{smcl}
{txt}{sf}{ul off}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\lSMS ISA\dofile\Submission\S11_S18_balance.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 5 Apr 2024, 11:07:36
{txt}
{com}. use  NER_panel_data.dta, clear
{txt}
{com}. gen country=1
{txt}
{com}. append using NIGERIA_panel_data.dta
{txt}
{com}. replace country=2 if country ==.
{txt}(18,592 real changes made)

{com}. 
. append using ETHIOPIA_panel_data.dta
{txt}
{com}. replace country=3 if country ==.
{txt}(13,511 real changes made)

{com}. 
. append using UGA_panel_data.dta
{txt}
{com}. replace country=4 if country ==.
{txt}(20,313 real changes made)

{com}. 
. append using TZA_panel_data.dta
{txt}
{com}. replace country=5 if country ==.
{txt}(21,117 real changes made)

{com}. 
. append using MWI_panel_data.dta
{txt}
{com}. replace country=6 if country ==.
{txt}(9,163 real changes made)

{com}. 
. xtset HHID_panel year
{res}{txt}{col 8}panel variable:  {res}HHID_panel (unbalanced)
{txt}{col 9}time variable:  {res}{col 25}year, 2008 to 2019, but with gaps
{txt}{col 17}delta:  {res}1 unit
{txt}
{com}. 
. label define country 1 "Niger" 2 "Nigeria" 3 "Ethiopia" 4 "Uganda" 5 "Tanzania" 6 "Malawi"
{txt}
{com}. label values country country
{txt}
{com}. 
. gen dyear=1
{txt}
{com}. egen total_year=sum(dyear), by(HHID_panel)
{txt}
{com}. 
. 
. 
. gen balance=0
{txt}
{com}. replace balance=1 if total_year==2&country==1
{txt}(5,954 real changes made)

{com}. replace balance=1 if total_year==4&country==2
{txt}(4,812 real changes made)

{com}. replace balance=1 if total_year==3&country==3
{txt}(9,447 real changes made)

{com}. replace balance=1 if total_year==7&country==4
{txt}(7,805 real changes made)

{com}. replace balance=1 if total_year==5&country==5
{txt}(1,585 real changes made)

{com}. replace balance=1 if total_year==4&country==6
{txt}(5,604 real changes made)

{com}. tab country year

           {txt}{c |}                                                           year
   country {c |}      2008       2009       2010       2011       2012       2013       2014       2015       2016       2018       2019 {c |}     Total
{hline 11}{c +}{hline 121}{c +}{hline 10}
     Niger {c |}{res}         0          0          0      3,930          0          0      3,116          0          0          0          0 {txt}{c |}{res}     7,046 
{txt}   Nigeria {c |}{res}         0          0      4,801          0      4,724          0          0      4,504          0      4,563          0 {txt}{c |}{res}    18,592 
{txt}  Ethiopia {c |}{res}         0          0          0      3,786          0      5,037          0      4,688          0          0          0 {txt}{c |}{res}    13,511 
{txt}    Uganda {c |}{res}         0      2,837      2,570      2,751          0      3,028          0      3,131          0      3,052      2,944 {txt}{c |}{res}    20,313 
{txt}  Tanzania {c |}{res}     3,176          0      3,767          0      4,705          0      4,182          0          0          0      5,287 {txt}{c |}{res}    21,117 
{txt}    Malawi {c |}{res}         0          0      1,581          0          0      1,962          0          0      2,447          0      3,173 {txt}{c |}{res}     9,163 
{txt}{hline 11}{c +}{hline 121}{c +}{hline 10}
     Total {c |}{res}     3,176      2,837     12,719     10,467      9,429     10,027      7,298     12,323      2,447      7,615     11,404 {txt}{c |}{res}    89,742 
{txt}
{com}. 
. keep if balance==1
{txt}(54,535 observations deleted)

{com}. 
. 
. foreach x of varlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop hdd9 pdd9 no_species{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. 
. 
. 
. tab year, generate(year_)

       {txt}year {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
       2008 {c |}{res}        317        0.90        0.90
{txt}       2009 {c |}{res}      1,115        3.17        4.07
{txt}       2010 {c |}{res}      4,036       11.46       15.53
{txt}       2011 {c |}{res}      7,241       20.57       36.10
{txt}       2012 {c |}{res}      1,520        4.32       40.42
{txt}       2013 {c |}{res}      5,665       16.09       56.51
{txt}       2014 {c |}{res}      3,294        9.36       65.86
{txt}       2015 {c |}{res}      5,467       15.53       81.39
{txt}       2016 {c |}{res}      1,401        3.98       85.37
{txt}       2018 {c |}{res}      2,318        6.58       91.95
{txt}       2019 {c |}{res}      2,833        8.05      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}     35,207      100.00
{txt}
{com}. global year_NIGER year_4
{txt}
{com}. global year_NIGERIA year_3 year_5 year_8
{txt}
{com}. global year_ETHIOPIA year_6
{txt}
{com}. global year_UGANDA   year_3 year_4 year_6 year_8 year_10
{txt}
{com}. global year_TANZANIA year_1 year_5 year_7
{txt}
{com}. global year_MALAWI year_3 year_6 
{txt}
{com}. global xlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop  motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean
{txt}
{com}. 
. 
. 
. 
. 
. 
. 
. ********************************************************************************
. *                                   S11                                        *
. ********************************************************************************
. eststo clear
{txt}
{com}. xtreg hdd9  no_species   $xlist  no_species_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    35,207
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    10,162

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0381                                         {txt}min = {res}         2
{txt}     between = {res}0.5100                                         {txt}avg = {res}       3.5
{txt}     overall = {res}0.3454                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 13091.27
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:10,162} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0362596{col 30}{space 2} .0038942{col 41}{space 1}    9.31{col 50}{space 3}0.000{col 58}{space 4}  .028627{col 71}{space 3} .0438922
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0005398{col 30}{space 2} .0036333{col 41}{space 1}    0.15{col 50}{space 3}0.882{col 58}{space 4}-.0065814{col 71}{space 3} .0076609
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0034308{col 30}{space 2} .0384264{col 41}{space 1}    0.09{col 50}{space 3}0.929{col 58}{space 4}-.0718835{col 71}{space 3} .0787451
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.000719{col 30}{space 2} .0006802{col 41}{space 1}   -1.06{col 50}{space 3}0.291{col 58}{space 4}-.0020522{col 71}{space 3} .0006142
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0111233{col 30}{space 2}  .023815{col 41}{space 1}   -0.47{col 50}{space 3}0.640{col 58}{space 4}-.0577999{col 71}{space 3} .0355534
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2478161{col 30}{space 2} .0202954{col 41}{space 1}   12.21{col 50}{space 3}0.000{col 58}{space 4} .2080378{col 71}{space 3} .2875944
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1417719{col 30}{space 2} .0383227{col 41}{space 1}    3.70{col 50}{space 3}0.000{col 58}{space 4} .0666607{col 71}{space 3} .2168831
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .166629{col 30}{space 2} .0240591{col 41}{space 1}    6.93{col 50}{space 3}0.000{col 58}{space 4} .1194741{col 71}{space 3} .2137839
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1824881{col 30}{space 2} .0289238{col 41}{space 1}    6.31{col 50}{space 3}0.000{col 58}{space 4} .1257985{col 71}{space 3} .2391777
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .139191{col 30}{space 2}  .026058{col 41}{space 1}    5.34{col 50}{space 3}0.000{col 58}{space 4} .0881182{col 71}{space 3} .1902637
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1725057{col 30}{space 2} .0224338{col 41}{space 1}    7.69{col 50}{space 3}0.000{col 58}{space 4} .1285362{col 71}{space 3} .2164752
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0954486{col 30}{space 2}  .018333{col 41}{space 1}   -5.21{col 50}{space 3}0.000{col 58}{space 4}-.1313806{col 71}{space 3}-.0595167
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0000502{col 30}{space 2} .0012952{col 41}{space 1}   -0.04{col 50}{space 3}0.969{col 58}{space 4}-.0025889{col 71}{space 3} .0024884
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0659112{col 30}{space 2} .0227311{col 41}{space 1}    2.90{col 50}{space 3}0.004{col 58}{space 4}  .021359{col 71}{space 3} .1104633
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0157428{col 30}{space 2} .0593399{col 41}{space 1}    0.27{col 50}{space 3}0.791{col 58}{space 4}-.1005612{col 71}{space 3} .1320469
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5771733{col 30}{space 2} .0397805{col 41}{space 1}   14.51{col 50}{space 3}0.000{col 58}{space 4} .4992049{col 71}{space 3} .6551417
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7236662{col 30}{space 2} .0457774{col 41}{space 1}   15.81{col 50}{space 3}0.000{col 58}{space 4} .6339442{col 71}{space 3} .8133882
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3741767{col 30}{space 2} .0459904{col 41}{space 1}    8.14{col 50}{space 3}0.000{col 58}{space 4} .2840371{col 71}{space 3} .4643162
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2084028{col 30}{space 2} .0362077{col 41}{space 1}    5.76{col 50}{space 3}0.000{col 58}{space 4}  .137437{col 71}{space 3} .2793686
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2} .0043767{col 30}{space 2} .0053319{col 41}{space 1}    0.82{col 50}{space 3}0.412{col 58}{space 4}-.0060736{col 71}{space 3} .0148271
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.3841461{col 30}{space 2} .0472303{col 41}{space 1}   -8.13{col 50}{space 3}0.000{col 58}{space 4}-.4767157{col 71}{space 3}-.2915766
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.455435{col 30}{space 2} .0399524{col 41}{space 1}  -36.43{col 50}{space 3}0.000{col 58}{space 4} -1.53374{col 71}{space 3} -1.37713
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.4548191{col 30}{space 2}  .043014{col 41}{space 1}  -10.57{col 50}{space 3}0.000{col 58}{space 4}-.5391251{col 71}{space 3}-.3705132
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.2349764{col 30}{space 2} .0635848{col 41}{space 1}   -3.70{col 50}{space 3}0.000{col 58}{space 4}-.3596004{col 71}{space 3}-.1103524
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .5594094{col 30}{space 2} .0458302{col 41}{space 1}   12.21{col 50}{space 3}0.000{col 58}{space 4} .4695838{col 71}{space 3} .6492349
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2} -.228921{col 30}{space 2} .0897557{col 41}{space 1}   -2.55{col 50}{space 3}0.011{col 58}{space 4}-.4048388{col 71}{space 3}-.0530031
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0692744{col 30}{space 2} .0813229{col 41}{space 1}   -0.85{col 50}{space 3}0.394{col 58}{space 4}-.2286645{col 71}{space 3} .0901156
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0925701{col 30}{space 2} .0828031{col 41}{space 1}    1.12{col 50}{space 3}0.264{col 58}{space 4}-.0697209{col 71}{space 3} .2548611
{txt}{space 11}2012  {c |}{col 18}{res}{space 2}  .054247{col 30}{space 2} .0832342{col 41}{space 1}    0.65{col 50}{space 3}0.515{col 58}{space 4} -.108889{col 71}{space 3}  .217383
{txt}{space 11}2013  {c |}{col 18}{res}{space 2}  .089477{col 30}{space 2}  .082858{col 41}{space 1}    1.08{col 50}{space 3}0.280{col 58}{space 4}-.0729216{col 71}{space 3} .2518756
{txt}{space 11}2014  {c |}{col 18}{res}{space 2} -.115592{col 30}{space 2}  .085837{col 41}{space 1}   -1.35{col 50}{space 3}0.178{col 58}{space 4}-.2838294{col 71}{space 3} .0526455
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .2341148{col 30}{space 2} .0831242{col 41}{space 1}    2.82{col 50}{space 3}0.005{col 58}{space 4} .0711943{col 71}{space 3} .3970352
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.1434308{col 30}{space 2} .0905341{col 41}{space 1}   -1.58{col 50}{space 3}0.113{col 58}{space 4}-.3208744{col 71}{space 3} .0340128
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .5257699{col 30}{space 2} .0857533{col 41}{space 1}    6.13{col 50}{space 3}0.000{col 58}{space 4} .3576966{col 71}{space 3} .6938432
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .1420295{col 30}{space 2} .0843597{col 41}{space 1}    1.68{col 50}{space 3}0.092{col 58}{space 4}-.0233124{col 71}{space 3} .3073714
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.495849{col 30}{space 2} .0991903{col 41}{space 1}   45.33{col 50}{space 3}0.000{col 58}{space 4}  4.30144{col 71}{space 3} 4.690258
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .70788532
         {txt}sigma_e {c |} {res} 1.2310526
             {txt}rho {c |} {res} .24848933{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,447
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,149

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0229                                         {txt}min = {res}         3
{txt}     between = {res}0.2905                                         {txt}avg = {res}       3.0
{txt}     overall = {res}0.1843                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}21{txt})     =  {res}  1438.63
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,149} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0188037{col 30}{space 2} .0056495{col 41}{space 1}    3.33{col 50}{space 3}0.001{col 58}{space 4} .0077309{col 71}{space 3} .0298766
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0356371{col 30}{space 2}  .007875{col 41}{space 1}    4.53{col 50}{space 3}0.000{col 58}{space 4} .0202025{col 71}{space 3} .0510718
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0137169{col 30}{space 2} .0650678{col 41}{space 1}   -0.21{col 50}{space 3}0.833{col 58}{space 4}-.1412474{col 71}{space 3} .1138136
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0032653{col 30}{space 2} .0011193{col 41}{space 1}   -2.92{col 50}{space 3}0.004{col 58}{space 4}-.0054591{col 71}{space 3}-.0010714
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0222504{col 30}{space 2} .0414839{col 41}{space 1}    0.54{col 50}{space 3}0.592{col 58}{space 4}-.0590566{col 71}{space 3} .1035573
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3225846{col 30}{space 2} .0334905{col 41}{space 1}    9.63{col 50}{space 3}0.000{col 58}{space 4} .2569444{col 71}{space 3} .3882249
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2046082{col 30}{space 2} .1576145{col 41}{space 1}   -1.30{col 50}{space 3}0.194{col 58}{space 4}-.5135269{col 71}{space 3} .1043105
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1995502{col 30}{space 2} .0387906{col 41}{space 1}    5.14{col 50}{space 3}0.000{col 58}{space 4} .1235219{col 71}{space 3} .2755784
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1330424{col 30}{space 2} .0477661{col 41}{space 1}    2.79{col 50}{space 3}0.005{col 58}{space 4} .0394225{col 71}{space 3} .2266623
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0721699{col 30}{space 2} .0713957{col 41}{space 1}    1.01{col 50}{space 3}0.312{col 58}{space 4}-.0677632{col 71}{space 3} .2121029
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2105658{col 30}{space 2} .0515772{col 41}{space 1}    4.08{col 50}{space 3}0.000{col 58}{space 4} .1094763{col 71}{space 3} .3116552
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1543033{col 30}{space 2} .0312073{col 41}{space 1}   -4.94{col 50}{space 3}0.000{col 58}{space 4}-.2154684{col 71}{space 3}-.0931382
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0104794{col 30}{space 2} .0037804{col 41}{space 1}    2.77{col 50}{space 3}0.006{col 58}{space 4} .0030699{col 71}{space 3}  .017889
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2276331{col 30}{space 2} .0344267{col 41}{space 1}    6.61{col 50}{space 3}0.000{col 58}{space 4} .1601579{col 71}{space 3} .2951082
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} 1.108815{col 30}{space 2} .3082253{col 41}{space 1}    3.60{col 50}{space 3}0.000{col 58}{space 4} .5047044{col 71}{space 3} 1.712925
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .386694{col 30}{space 2} .0625885{col 41}{space 1}    6.18{col 50}{space 3}0.000{col 58}{space 4} .2640228{col 71}{space 3} .5093652
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3612632{col 30}{space 2} .0758498{col 41}{space 1}    4.76{col 50}{space 3}0.000{col 58}{space 4} .2126003{col 71}{space 3} .5099261
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4921992{col 30}{space 2} .1336323{col 41}{space 1}    3.68{col 50}{space 3}0.000{col 58}{space 4} .2302847{col 71}{space 3} .7541136
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1354545{col 30}{space 2} .0688526{col 41}{space 1}    1.97{col 50}{space 3}0.049{col 58}{space 4} .0005059{col 71}{space 3} .2704031
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2} .0192621{col 30}{space 2} .0073562{col 41}{space 1}    2.62{col 50}{space 3}0.009{col 58}{space 4} .0048441{col 71}{space 3}   .03368
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.2131726{col 30}{space 2} .0244027{col 41}{space 1}   -8.74{col 50}{space 3}0.000{col 58}{space 4} -.261001{col 71}{space 3}-.1653441
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.248182{col 30}{space 2} .0821586{col 41}{space 1}   39.54{col 50}{space 3}0.000{col 58}{space 4} 3.087154{col 71}{space 3}  3.40921
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .6820681
         {txt}sigma_e {c |} {res} 1.0652094
             {txt}rho {c |} {res} .29078092{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,604
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,401

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0382                                         {txt}min = {res}         4
{txt}     between = {res}0.5221                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.3146                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}22{txt})     =  {res}  2141.20
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,401} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0907065{col 30}{space 2} .0112519{col 41}{space 1}    8.06{col 50}{space 3}0.000{col 58}{space 4} .0686532{col 71}{space 3} .1127597
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0101281{col 30}{space 2} .0104812{col 41}{space 1}   -0.97{col 50}{space 3}0.334{col 58}{space 4}-.0306708{col 71}{space 3} .0104147
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1929403{col 30}{space 2} .0907565{col 41}{space 1}   -2.13{col 50}{space 3}0.034{col 58}{space 4}-.3708197{col 71}{space 3}-.0150609
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0014955{col 30}{space 2} .0016501{col 41}{space 1}   -0.91{col 50}{space 3}0.365{col 58}{space 4}-.0047297{col 71}{space 3} .0017386
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1403699{col 30}{space 2} .0550202{col 41}{space 1}   -2.55{col 50}{space 3}0.011{col 58}{space 4}-.2482074{col 71}{space 3}-.0325324
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .253763{col 30}{space 2} .0553667{col 41}{space 1}    4.58{col 50}{space 3}0.000{col 58}{space 4} .1452462{col 71}{space 3} .3622797
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2193902{col 30}{space 2} .1599716{col 41}{space 1}    1.37{col 50}{space 3}0.170{col 58}{space 4}-.0941482{col 71}{space 3} .5329287
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1574912{col 30}{space 2} .0617282{col 41}{space 1}    2.55{col 50}{space 3}0.011{col 58}{space 4} .0365061{col 71}{space 3} .2784763
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4788726{col 30}{space 2} .1046595{col 41}{space 1}    4.58{col 50}{space 3}0.000{col 58}{space 4} .2737438{col 71}{space 3} .6840014
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1535169{col 30}{space 2} .0656077{col 41}{space 1}    2.34{col 50}{space 3}0.019{col 58}{space 4} .0249282{col 71}{space 3} .2821056
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2614808{col 30}{space 2} .0473752{col 41}{space 1}    5.52{col 50}{space 3}0.000{col 58}{space 4} .1686271{col 71}{space 3} .3543346
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1802004{col 30}{space 2} .0404302{col 41}{space 1}   -4.46{col 50}{space 3}0.000{col 58}{space 4}-.2594421{col 71}{space 3}-.1009586
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0046813{col 30}{space 2} .0311389{col 41}{space 1}   -0.15{col 50}{space 3}0.881{col 58}{space 4}-.0657124{col 71}{space 3} .0563499
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} -.059823{col 30}{space 2} .0575085{col 41}{space 1}   -1.04{col 50}{space 3}0.298{col 58}{space 4}-.1725375{col 71}{space 3} .0528915
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1151374{col 30}{space 2} .3077044{col 41}{space 1}    0.37{col 50}{space 3}0.708{col 58}{space 4}-.4879521{col 71}{space 3}  .718227
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7471413{col 30}{space 2}  .105058{col 41}{space 1}    7.11{col 50}{space 3}0.000{col 58}{space 4} .5412315{col 71}{space 3} .9530511
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7978171{col 30}{space 2} .1454013{col 41}{space 1}    5.49{col 50}{space 3}0.000{col 58}{space 4} .5128359{col 71}{space 3} 1.082798
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4715859{col 30}{space 2} .1025445{col 41}{space 1}    4.60{col 50}{space 3}0.000{col 58}{space 4} .2706024{col 71}{space 3} .6725695
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3749479{col 30}{space 2} .0973078{col 41}{space 1}    3.85{col 50}{space 3}0.000{col 58}{space 4} .1842281{col 71}{space 3} .5656677
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2} -.026969{col 30}{space 2} .0178037{col 41}{space 1}   -1.51{col 50}{space 3}0.130{col 58}{space 4}-.0618637{col 71}{space 3} .0079257
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .1433252{col 30}{space 2} .0494833{col 41}{space 1}    2.90{col 50}{space 3}0.004{col 58}{space 4} .0463397{col 71}{space 3} .2403107
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0665313{col 30}{space 2} .0421882{col 41}{space 1}    1.58{col 50}{space 3}0.115{col 58}{space 4}-.0161561{col 71}{space 3} .1492187
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  4.93149{col 30}{space 2} .1335364{col 41}{space 1}   36.93{col 50}{space 3}0.000{col 58}{space 4} 4.669764{col 71}{space 3} 5.193217
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .63629319
         {txt}sigma_e {c |} {res} 1.2883631
             {txt}rho {c |} {res} .19608635{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,954
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,977

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0458                                         {txt}min = {res}         2
{txt}     between = {res}0.2824                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.1994                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}21{txt})     =  {res}  1335.62
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,977} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .1410896{col 30}{space 2} .0176447{col 41}{space 1}    8.00{col 50}{space 3}0.000{col 58}{space 4} .1065066{col 71}{space 3} .1756726
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0094576{col 30}{space 2} .0070389{col 41}{space 1}    1.34{col 50}{space 3}0.179{col 58}{space 4}-.0043385{col 71}{space 3} .0232536
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0278319{col 30}{space 2} .1080215{col 41}{space 1}   -0.26{col 50}{space 3}0.797{col 58}{space 4}-.2395501{col 71}{space 3} .1838862
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0026285{col 30}{space 2} .0015326{col 41}{space 1}    1.72{col 50}{space 3}0.086{col 58}{space 4}-.0003753{col 71}{space 3} .0056323
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0911861{col 30}{space 2} .0629183{col 41}{space 1}    1.45{col 50}{space 3}0.147{col 58}{space 4}-.0321314{col 71}{space 3} .2145037
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2938853{col 30}{space 2} .0480995{col 41}{space 1}    6.11{col 50}{space 3}0.000{col 58}{space 4}  .199612{col 71}{space 3} .3881586
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .250924{col 30}{space 2} .0965768{col 41}{space 1}    2.60{col 50}{space 3}0.009{col 58}{space 4} .0616369{col 71}{space 3}  .440211
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1031293{col 30}{space 2} .0745571{col 41}{space 1}    1.38{col 50}{space 3}0.167{col 58}{space 4}-.0429999{col 71}{space 3} .2492584
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .224112{col 30}{space 2} .1070713{col 41}{space 1}    2.09{col 50}{space 3}0.036{col 58}{space 4}  .014256{col 71}{space 3}  .433968
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1977952{col 30}{space 2} .0848799{col 41}{space 1}    2.33{col 50}{space 3}0.020{col 58}{space 4} .0314338{col 71}{space 3} .3641567
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1994156{col 30}{space 2} .0653974{col 41}{space 1}   -3.05{col 50}{space 3}0.002{col 58}{space 4}-.3275922{col 71}{space 3} -.071239
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1285839{col 30}{space 2} .0480644{col 41}{space 1}   -2.68{col 50}{space 3}0.007{col 58}{space 4}-.2227884{col 71}{space 3}-.0343794
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0011633{col 30}{space 2} .0018088{col 41}{space 1}   -0.64{col 50}{space 3}0.520{col 58}{space 4}-.0047084{col 71}{space 3} .0023819
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0588329{col 30}{space 2} .2379057{col 41}{space 1}    0.25{col 50}{space 3}0.805{col 58}{space 4}-.4074537{col 71}{space 3} .5251196
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1513718{col 30}{space 2} .1254584{col 41}{space 1}    1.21{col 50}{space 3}0.228{col 58}{space 4}-.0945221{col 71}{space 3} .3972656
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3955978{col 30}{space 2} .0972305{col 41}{space 1}    4.07{col 50}{space 3}0.000{col 58}{space 4} .2050295{col 71}{space 3}  .586166
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .550598{col 30}{space 2} .1303039{col 41}{space 1}    4.23{col 50}{space 3}0.000{col 58}{space 4}  .295207{col 71}{space 3}  .805989
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2370543{col 30}{space 2} .1108884{col 41}{space 1}    2.14{col 50}{space 3}0.033{col 58}{space 4} .0197169{col 71}{space 3} .4543916
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .5300457{col 30}{space 2} .0855889{col 41}{space 1}    6.19{col 50}{space 3}0.000{col 58}{space 4} .3622946{col 71}{space 3} .6977968
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.1464253{col 30}{space 2} .0206657{col 41}{space 1}   -7.09{col 50}{space 3}0.000{col 58}{space 4}-.1869294{col 71}{space 3}-.1059213
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2602046{col 30}{space 2} .0386347{col 41}{space 1}    6.73{col 50}{space 3}0.000{col 58}{space 4} .1844819{col 71}{space 3} .3359272
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.485651{col 30}{space 2} .1216877{col 41}{space 1}   36.86{col 50}{space 3}0.000{col 58}{space 4} 4.247147{col 71}{space 3} 4.724154
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .61209539
         {txt}sigma_e {c |} {res} 1.3666293
             {txt}rho {c |} {res}   .167085{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,812
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,203

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0699                                         {txt}min = {res}         4
{txt}     between = {res}0.4040                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.2550                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1159.50
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,203} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0370702{col 30}{space 2} .0132604{col 41}{space 1}    2.80{col 50}{space 3}0.005{col 58}{space 4} .0110803{col 71}{space 3}   .06306
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0009992{col 30}{space 2} .0083766{col 41}{space 1}   -0.12{col 50}{space 3}0.905{col 58}{space 4}-.0174171{col 71}{space 3} .0154187
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .082194{col 30}{space 2} .0973559{col 41}{space 1}    0.84{col 50}{space 3}0.399{col 58}{space 4}  -.10862{col 71}{space 3} .2730079
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0069539{col 30}{space 2} .0018591{col 41}{space 1}    3.74{col 50}{space 3}0.000{col 58}{space 4} .0033101{col 71}{space 3} .0105977
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0765073{col 30}{space 2} .0691222{col 41}{space 1}    1.11{col 50}{space 3}0.268{col 58}{space 4}-.0589696{col 71}{space 3} .2119843
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0465421{col 30}{space 2} .0502572{col 41}{space 1}    0.93{col 50}{space 3}0.354{col 58}{space 4}-.0519602{col 71}{space 3} .1450444
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1038281{col 30}{space 2}  .065264{col 41}{space 1}    1.59{col 50}{space 3}0.112{col 58}{space 4} -.024087{col 71}{space 3} .2317431
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1767086{col 30}{space 2} .0650376{col 41}{space 1}    2.72{col 50}{space 3}0.007{col 58}{space 4} .0492372{col 71}{space 3} .3041799
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1216326{col 30}{space 2} .0808485{col 41}{space 1}    1.50{col 50}{space 3}0.132{col 58}{space 4}-.0368275{col 71}{space 3} .2800927
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2753345{col 30}{space 2} .0816545{col 41}{space 1}    3.37{col 50}{space 3}0.001{col 58}{space 4} .1152946{col 71}{space 3} .4353743
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2644773{col 30}{space 2} .0610981{col 41}{space 1}    4.33{col 50}{space 3}0.000{col 58}{space 4} .1447271{col 71}{space 3} .3842275
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0162226{col 30}{space 2} .0894361{col 41}{space 1}    0.18{col 50}{space 3}0.856{col 58}{space 4} -.159069{col 71}{space 3} .1915142
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0010789{col 30}{space 2}  .013163{col 41}{space 1}   -0.08{col 50}{space 3}0.935{col 58}{space 4}-.0268779{col 71}{space 3} .0247201
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1357412{col 30}{space 2} .1168714{col 41}{space 1}    1.16{col 50}{space 3}0.245{col 58}{space 4}-.0933226{col 71}{space 3}  .364805
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.2119674{col 30}{space 2} .1086129{col 41}{space 1}   -1.95{col 50}{space 3}0.051{col 58}{space 4}-.4248447{col 71}{space 3} .0009099
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} 1.119476{col 30}{space 2} .1292772{col 41}{space 1}    8.66{col 50}{space 3}0.000{col 58}{space 4} .8660977{col 71}{space 3} 1.372855
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7018546{col 30}{space 2} .1210752{col 41}{space 1}    5.80{col 50}{space 3}0.000{col 58}{space 4} .4645514{col 71}{space 3} .9391577
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0895194{col 30}{space 2} .1290458{col 41}{space 1}    0.69{col 50}{space 3}0.488{col 58}{space 4}-.1634057{col 71}{space 3} .3424444
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0896756{col 30}{space 2} .1008824{col 41}{space 1}   -0.89{col 50}{space 3}0.374{col 58}{space 4}-.2874014{col 71}{space 3} .1080503
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0661552{col 30}{space 2} .0207075{col 41}{space 1}   -3.19{col 50}{space 3}0.001{col 58}{space 4}-.1067412{col 71}{space 3}-.0255692
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.6498317{col 30}{space 2} .0562512{col 41}{space 1}  -11.55{col 50}{space 3}0.000{col 58}{space 4}-.7600821{col 71}{space 3}-.5395813
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.4897743{col 30}{space 2} .0544097{col 41}{space 1}   -9.00{col 50}{space 3}0.000{col 58}{space 4}-.5964154{col 71}{space 3}-.3831332
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3756473{col 30}{space 2} .0513192{col 41}{space 1}   -7.32{col 50}{space 3}0.000{col 58}{space 4} -.476231{col 71}{space 3}-.2750636
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  4.47321{col 30}{space 2} .1650935{col 41}{space 1}   27.10{col 50}{space 3}0.000{col 58}{space 4} 4.149632{col 71}{space 3} 4.796787
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .72865478
         {txt}sigma_e {c |} {res} 1.2514147
             {txt}rho {c |} {res} .25319204{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     1,585
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}       317

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0256                                         {txt}min = {res}         5
{txt}     between = {res}0.4862                                         {txt}avg = {res}       5.0
{txt}     overall = {res}0.2771                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}23{txt})     =  {res}   366.66
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:317} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0360088{col 30}{space 2} .0154353{col 41}{space 1}    2.33{col 50}{space 3}0.020{col 58}{space 4} .0057561{col 71}{space 3} .0662615
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0480401{col 30}{space 2} .0181754{col 41}{space 1}   -2.64{col 50}{space 3}0.008{col 58}{space 4}-.0836633{col 71}{space 3}-.0124169
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1429927{col 30}{space 2} .1951737{col 41}{space 1}    0.73{col 50}{space 3}0.464{col 58}{space 4}-.2395408{col 71}{space 3} .5255261
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0098685{col 30}{space 2} .0037408{col 41}{space 1}   -2.64{col 50}{space 3}0.008{col 58}{space 4}-.0172004{col 71}{space 3}-.0025366
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2046457{col 30}{space 2} .1174492{col 41}{space 1}    1.74{col 50}{space 3}0.081{col 58}{space 4}-.0255504{col 71}{space 3} .4348418
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0824875{col 30}{space 2} .1202147{col 41}{space 1}    0.69{col 50}{space 3}0.493{col 58}{space 4}-.1531289{col 71}{space 3}  .318104
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3303173{col 30}{space 2} .1463725{col 41}{space 1}    2.26{col 50}{space 3}0.024{col 58}{space 4} .0434325{col 71}{space 3} .6172021
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1713237{col 30}{space 2} .1028566{col 41}{space 1}    1.67{col 50}{space 3}0.096{col 58}{space 4}-.0302717{col 71}{space 3}  .372919
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0948617{col 30}{space 2} .1106733{col 41}{space 1}    0.86{col 50}{space 3}0.391{col 58}{space 4} -.122054{col 71}{space 3} .3117774
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1158384{col 30}{space 2} .0798176{col 41}{space 1}    1.45{col 50}{space 3}0.147{col 58}{space 4}-.0406013{col 71}{space 3} .2722781
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3231793{col 30}{space 2} .0900045{col 41}{space 1}    3.59{col 50}{space 3}0.000{col 58}{space 4} .1467738{col 71}{space 3} .4995848
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.135986{col 30}{space 2} .0947163{col 41}{space 1}   -1.44{col 50}{space 3}0.151{col 58}{space 4}-.3216264{col 71}{space 3} .0496545
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0055268{col 30}{space 2} .0146438{col 41}{space 1}   -0.38{col 50}{space 3}0.706{col 58}{space 4} -.034228{col 71}{space 3} .0231745
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.1343349{col 30}{space 2} .0892011{col 41}{space 1}   -1.51{col 50}{space 3}0.132{col 58}{space 4}-.3091659{col 71}{space 3} .0404961
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0761289{col 30}{space 2} .3026768{col 41}{space 1}    0.25{col 50}{space 3}0.801{col 58}{space 4}-.5171068{col 71}{space 3} .6693646
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} 1.053775{col 30}{space 2} .2202081{col 41}{space 1}    4.79{col 50}{space 3}0.000{col 58}{space 4} .6221754{col 71}{space 3} 1.485375
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.275051{col 30}{space 2} .2177714{col 41}{space 1}    5.85{col 50}{space 3}0.000{col 58}{space 4} .8482273{col 71}{space 3} 1.701876
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1522866{col 30}{space 2}   .18465{col 41}{space 1}   -0.82{col 50}{space 3}0.410{col 58}{space 4}-.5141939{col 71}{space 3} .2096207
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} -.126549{col 30}{space 2} .1968658{col 41}{space 1}   -0.64{col 50}{space 3}0.520{col 58}{space 4}-.5123989{col 71}{space 3} .2593009
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2} .0500661{col 30}{space 2} .0236061{col 41}{space 1}    2.12{col 50}{space 3}0.034{col 58}{space 4} .0037989{col 71}{space 3} .0963333
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.0626493{col 30}{space 2}  .098786{col 41}{space 1}   -0.63{col 50}{space 3}0.526{col 58}{space 4}-.2562664{col 71}{space 3} .1309678
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0354334{col 30}{space 2} .0834407{col 41}{space 1}   -0.42{col 50}{space 3}0.671{col 58}{space 4}-.1989743{col 71}{space 3} .1281074
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0999455{col 30}{space 2} .0837435{col 41}{space 1}    1.19{col 50}{space 3}0.233{col 58}{space 4}-.0641888{col 71}{space 3} .2640797
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.699859{col 30}{space 2} .3149333{col 41}{space 1}   14.92{col 50}{space 3}0.000{col 58}{space 4} 4.082601{col 71}{space 3} 5.317117
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .68514864
         {txt}sigma_e {c |} {res}  1.219869
             {txt}rho {c |} {res}  .2398092{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. xtreg hdd9  no_species   $xlist  no_species_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,805
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,115

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0725                                         {txt}min = {res}         7
{txt}     between = {res}0.3418                                         {txt}avg = {res}       7.0
{txt}     overall = {res}0.1878                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}25{txt})     =  {res}  1126.63
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,115} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0496821{col 30}{space 2} .0076113{col 41}{space 1}    6.53{col 50}{space 3}0.000{col 58}{space 4} .0347642{col 71}{space 3}    .0646
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0066351{col 30}{space 2} .0081645{col 41}{space 1}   -0.81{col 50}{space 3}0.416{col 58}{space 4}-.0226371{col 71}{space 3} .0093669
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1618849{col 30}{space 2} .0849919{col 41}{space 1}    1.90{col 50}{space 3}0.057{col 58}{space 4}-.0046962{col 71}{space 3} .3284659
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}  .000158{col 30}{space 2} .0017805{col 41}{space 1}    0.09{col 50}{space 3}0.929{col 58}{space 4}-.0033316{col 71}{space 3} .0036477
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0184619{col 30}{space 2} .0518388{col 41}{space 1}    0.36{col 50}{space 3}0.722{col 58}{space 4}-.0831403{col 71}{space 3} .1200641
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2462377{col 30}{space 2} .0488554{col 41}{space 1}    5.04{col 50}{space 3}0.000{col 58}{space 4} .1504828{col 71}{space 3} .3419926
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1496219{col 30}{space 2}  .066516{col 41}{space 1}    2.25{col 50}{space 3}0.024{col 58}{space 4} .0192529{col 71}{space 3}  .279991
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2951898{col 30}{space 2} .0481286{col 41}{space 1}    6.13{col 50}{space 3}0.000{col 58}{space 4} .2008594{col 71}{space 3} .3895202
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3818126{col 30}{space 2} .0482827{col 41}{space 1}    7.91{col 50}{space 3}0.000{col 58}{space 4} .2871802{col 71}{space 3}  .476445
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0737052{col 30}{space 2} .0395648{col 41}{space 1}    1.86{col 50}{space 3}0.062{col 58}{space 4}-.0038404{col 71}{space 3} .1512507
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1702151{col 30}{space 2} .0409918{col 41}{space 1}    4.15{col 50}{space 3}0.000{col 58}{space 4} .0898728{col 71}{space 3} .2505575
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0033165{col 30}{space 2} .0344403{col 41}{space 1}   -0.10{col 50}{space 3}0.923{col 58}{space 4}-.0708181{col 71}{space 3} .0641852
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0012208{col 30}{space 2} .0013738{col 41}{space 1}    0.89{col 50}{space 3}0.374{col 58}{space 4}-.0014717{col 71}{space 3} .0039133
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} -.091776{col 30}{space 2} .0415746{col 41}{space 1}   -2.21{col 50}{space 3}0.027{col 58}{space 4}-.1732608{col 71}{space 3}-.0102912
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2037357{col 30}{space 2} .1314676{col 41}{space 1}    1.55{col 50}{space 3}0.121{col 58}{space 4}-.0539361{col 71}{space 3} .4614075
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3541438{col 30}{space 2} .1075765{col 41}{space 1}    3.29{col 50}{space 3}0.001{col 58}{space 4} .1432977{col 71}{space 3} .5649899
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5986489{col 30}{space 2} .1260923{col 41}{space 1}    4.75{col 50}{space 3}0.000{col 58}{space 4} .3515125{col 71}{space 3} .8457852
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1547028{col 30}{space 2} .1001673{col 41}{space 1}    1.54{col 50}{space 3}0.122{col 58}{space 4}-.0416214{col 71}{space 3}  .351027
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3039128{col 30}{space 2} .0894657{col 41}{space 1}    3.40{col 50}{space 3}0.001{col 58}{space 4} .1285632{col 71}{space 3} .4792624
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2} .0022564{col 30}{space 2} .0127804{col 41}{space 1}    0.18{col 50}{space 3}0.860{col 58}{space 4}-.0227927{col 71}{space 3} .0273056
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.2046375{col 30}{space 2} .0483068{col 41}{space 1}   -4.24{col 50}{space 3}0.000{col 58}{space 4}-.2993171{col 71}{space 3}-.1099579
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.1064379{col 30}{space 2} .0458956{col 41}{space 1}   -2.32{col 50}{space 3}0.020{col 58}{space 4}-.1963917{col 71}{space 3}-.0164841
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .4302819{col 30}{space 2} .0454428{col 41}{space 1}    9.47{col 50}{space 3}0.000{col 58}{space 4} .3412156{col 71}{space 3} .5193482
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1446756{col 30}{space 2} .0461272{col 41}{space 1}    3.14{col 50}{space 3}0.002{col 58}{space 4}  .054268{col 71}{space 3} .2350832
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .3992745{col 30}{space 2} .0447729{col 41}{space 1}    8.92{col 50}{space 3}0.000{col 58}{space 4} .3115212{col 71}{space 3} .4870278
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.009771{col 30}{space 2} .1566574{col 41}{space 1}   25.60{col 50}{space 3}0.000{col 58}{space 4} 3.702728{col 71}{space 3} 4.316814
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .68386739
         {txt}sigma_e {c |} {res} 1.2408796
             {txt}rho {c |} {res} .23296872{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. 
. esttab using  S11_balance.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(no_species   $xlist  no_species_mean _cons)
{res}{txt}(note: file S11_balance.rtf not found)
(output written to {browse  `"S11_balance.rtf"'})

{com}. 
. 
. 
. 
. 
. 
. ********************************************************************************
. *                                   S12                                        *
. ********************************************************************************
. eststo clear
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist   pdd9_mean i.country i.year, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    35,207
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    10,162

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0394                                         {txt}min = {res}         2
{txt}     between = {res}0.5117                                         {txt}avg = {res}       3.5
{txt}     overall = {res}0.3468                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 13327.14
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:10,162} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0819308{col 30}{space 2} .0070998{col 41}{space 1}   11.54{col 50}{space 3}0.000{col 58}{space 4} .0680154{col 71}{space 3} .0958463
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0004225{col 30}{space 2} .0036161{col 41}{space 1}    0.12{col 50}{space 3}0.907{col 58}{space 4}-.0066649{col 71}{space 3}   .00751
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0060057{col 30}{space 2}  .038339{col 41}{space 1}   -0.16{col 50}{space 3}0.876{col 58}{space 4}-.0811488{col 71}{space 3} .0691375
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0006217{col 30}{space 2} .0006782{col 41}{space 1}   -0.92{col 50}{space 3}0.359{col 58}{space 4}-.0019509{col 71}{space 3} .0007076
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0127374{col 30}{space 2}   .02375{col 41}{space 1}   -0.54{col 50}{space 3}0.592{col 58}{space 4}-.0592865{col 71}{space 3} .0338118
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2477989{col 30}{space 2} .0202477{col 41}{space 1}   12.24{col 50}{space 3}0.000{col 58}{space 4} .2081142{col 71}{space 3} .2874837
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}   .14047{col 30}{space 2} .0383124{col 41}{space 1}    3.67{col 50}{space 3}0.000{col 58}{space 4} .0653791{col 71}{space 3}  .215561
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1645205{col 30}{space 2} .0240738{col 41}{space 1}    6.83{col 50}{space 3}0.000{col 58}{space 4} .1173368{col 71}{space 3} .2117042
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1814588{col 30}{space 2} .0289108{col 41}{space 1}    6.28{col 50}{space 3}0.000{col 58}{space 4} .1247947{col 71}{space 3}  .238123
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1402889{col 30}{space 2} .0260158{col 41}{space 1}    5.39{col 50}{space 3}0.000{col 58}{space 4}  .089299{col 71}{space 3} .1912789
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .172909{col 30}{space 2} .0224034{col 41}{space 1}    7.72{col 50}{space 3}0.000{col 58}{space 4} .1289992{col 71}{space 3} .2168189
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}    -.101{col 30}{space 2}   .01833{col 41}{space 1}   -5.51{col 50}{space 3}0.000{col 58}{space 4}-.1369261{col 71}{space 3}-.0650739
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0001225{col 30}{space 2} .0012907{col 41}{space 1}   -0.09{col 50}{space 3}0.924{col 58}{space 4}-.0026523{col 71}{space 3} .0024072
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1012247{col 30}{space 2} .0215473{col 41}{space 1}    4.70{col 50}{space 3}0.000{col 58}{space 4} .0589927{col 71}{space 3} .1434566
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0103798{col 30}{space 2} .0593997{col 41}{space 1}    0.17{col 50}{space 3}0.861{col 58}{space 4}-.1060415{col 71}{space 3}  .126801
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5776411{col 30}{space 2} .0397441{col 41}{space 1}   14.53{col 50}{space 3}0.000{col 58}{space 4}  .499744{col 71}{space 3} .6555381
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7402021{col 30}{space 2} .0459739{col 41}{space 1}   16.10{col 50}{space 3}0.000{col 58}{space 4} .6500949{col 71}{space 3} .8303093
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .386488{col 30}{space 2} .0462192{col 41}{space 1}    8.36{col 50}{space 3}0.000{col 58}{space 4}    .2959{col 71}{space 3} .4770759
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2138417{col 30}{space 2} .0361725{col 41}{space 1}    5.91{col 50}{space 3}0.000{col 58}{space 4} .1429449{col 71}{space 3} .2847384
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0082174{col 30}{space 2} .0107903{col 41}{space 1}    0.76{col 50}{space 3}0.446{col 58}{space 4}-.0129312{col 71}{space 3}  .029366
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.3958598{col 30}{space 2} .0471247{col 41}{space 1}   -8.40{col 50}{space 3}0.000{col 58}{space 4}-.4882226{col 71}{space 3} -.303497
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.475197{col 30}{space 2} .0398851{col 41}{space 1}  -36.99{col 50}{space 3}0.000{col 58}{space 4}-1.553371{col 71}{space 3}-1.397024
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.5004761{col 30}{space 2} .0437752{col 41}{space 1}  -11.43{col 50}{space 3}0.000{col 58}{space 4} -.586274{col 71}{space 3}-.4146782
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2} -.285134{col 30}{space 2} .0652066{col 41}{space 1}   -4.37{col 50}{space 3}0.000{col 58}{space 4}-.4129366{col 71}{space 3}-.1573313
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .4919574{col 30}{space 2} .0462547{col 41}{space 1}   10.64{col 50}{space 3}0.000{col 58}{space 4} .4012997{col 71}{space 3}  .582615
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.1911919{col 30}{space 2} .0893279{col 41}{space 1}   -2.14{col 50}{space 3}0.032{col 58}{space 4}-.3662714{col 71}{space 3}-.0161123
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0450202{col 30}{space 2} .0808308{col 41}{space 1}   -0.56{col 50}{space 3}0.578{col 58}{space 4}-.2034457{col 71}{space 3} .1134053
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .1062407{col 30}{space 2} .0822075{col 41}{space 1}    1.29{col 50}{space 3}0.196{col 58}{space 4} -.054883{col 71}{space 3} .2673644
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0708896{col 30}{space 2} .0825849{col 41}{space 1}    0.86{col 50}{space 3}0.391{col 58}{space 4}-.0909739{col 71}{space 3} .2327531
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1010911{col 30}{space 2} .0822555{col 41}{space 1}    1.23{col 50}{space 3}0.219{col 58}{space 4}-.0601267{col 71}{space 3} .2623088
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.1043819{col 30}{space 2} .0851831{col 41}{space 1}   -1.23{col 50}{space 3}0.220{col 58}{space 4}-.2713376{col 71}{space 3} .0625739
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .2404732{col 30}{space 2} .0825369{col 41}{space 1}    2.91{col 50}{space 3}0.004{col 58}{space 4}  .078704{col 71}{space 3} .4022425
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.1269335{col 30}{space 2} .0901103{col 41}{space 1}   -1.41{col 50}{space 3}0.159{col 58}{space 4}-.3035464{col 71}{space 3} .0496794
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .5249815{col 30}{space 2} .0851957{col 41}{space 1}    6.16{col 50}{space 3}0.000{col 58}{space 4}  .358001{col 71}{space 3} .6919621
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .1420527{col 30}{space 2} .0838228{col 41}{space 1}    1.69{col 50}{space 3}0.090{col 58}{space 4} -.022237{col 71}{space 3} .3063424
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.442971{col 30}{space 2} .0989241{col 41}{space 1}   44.91{col 50}{space 3}0.000{col 58}{space 4} 4.249083{col 71}{space 3} 4.636859
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .70574938
         {txt}sigma_e {c |} {res} 1.2302401
             {txt}rho {c |} {res} .24760833{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,447
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,149

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0250                                         {txt}min = {res}         3
{txt}     between = {res}0.3029                                         {txt}avg = {res}       3.0
{txt}     overall = {res}0.1930                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}21{txt})     =  {res}  1567.73
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,149} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0541557{col 30}{space 2} .0109596{col 41}{space 1}    4.94{col 50}{space 3}0.000{col 58}{space 4} .0326753{col 71}{space 3} .0756362
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0305506{col 30}{space 2} .0078476{col 41}{space 1}    3.89{col 50}{space 3}0.000{col 58}{space 4} .0151697{col 71}{space 3} .0459315
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0253898{col 30}{space 2} .0646531{col 41}{space 1}   -0.39{col 50}{space 3}0.695{col 58}{space 4}-.1521075{col 71}{space 3} .1013279
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0030358{col 30}{space 2}  .001107{col 41}{space 1}   -2.74{col 50}{space 3}0.006{col 58}{space 4}-.0052056{col 71}{space 3}-.0008661
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0297094{col 30}{space 2} .0412218{col 41}{space 1}    0.72{col 50}{space 3}0.471{col 58}{space 4}-.0510837{col 71}{space 3} .1105026
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3165086{col 30}{space 2} .0332708{col 41}{space 1}    9.51{col 50}{space 3}0.000{col 58}{space 4}  .251299{col 71}{space 3} .3817183
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2239522{col 30}{space 2} .1583738{col 41}{space 1}   -1.41{col 50}{space 3}0.157{col 58}{space 4}-.5343591{col 71}{space 3} .0864547
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1962272{col 30}{space 2} .0387407{col 41}{space 1}    5.07{col 50}{space 3}0.000{col 58}{space 4} .1202969{col 71}{space 3} .2721576
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .125868{col 30}{space 2} .0477903{col 41}{space 1}    2.63{col 50}{space 3}0.008{col 58}{space 4} .0322008{col 71}{space 3} .2195353
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0752153{col 30}{space 2}  .071385{col 41}{space 1}    1.05{col 50}{space 3}0.292{col 58}{space 4}-.0646967{col 71}{space 3} .2151272
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2148737{col 30}{space 2} .0515776{col 41}{space 1}    4.17{col 50}{space 3}0.000{col 58}{space 4} .1137834{col 71}{space 3} .3159639
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1500895{col 30}{space 2} .0311931{col 41}{space 1}   -4.81{col 50}{space 3}0.000{col 58}{space 4}-.2112268{col 71}{space 3}-.0889523
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0087343{col 30}{space 2} .0037436{col 41}{space 1}    2.33{col 50}{space 3}0.020{col 58}{space 4} .0013969{col 71}{space 3} .0160716
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2103071{col 30}{space 2} .0320786{col 41}{space 1}    6.56{col 50}{space 3}0.000{col 58}{space 4} .1474341{col 71}{space 3} .2731801
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} 1.146671{col 30}{space 2} .3112322{col 41}{space 1}    3.68{col 50}{space 3}0.000{col 58}{space 4} .5366668{col 71}{space 3} 1.756675
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3956582{col 30}{space 2} .0622098{col 41}{space 1}    6.36{col 50}{space 3}0.000{col 58}{space 4} .2737292{col 71}{space 3} .5175871
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4119932{col 30}{space 2} .0755892{col 41}{space 1}    5.45{col 50}{space 3}0.000{col 58}{space 4} .2638412{col 71}{space 3} .5601453
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .5330268{col 30}{space 2} .1348467{col 41}{space 1}    3.95{col 50}{space 3}0.000{col 58}{space 4} .2687321{col 71}{space 3} .7973215
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1316368{col 30}{space 2} .0688355{col 41}{space 1}    1.91{col 50}{space 3}0.056{col 58}{space 4}-.0032783{col 71}{space 3} .2665518
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0749356{col 30}{space 2} .0160578{col 41}{space 1}    4.67{col 50}{space 3}0.000{col 58}{space 4} .0434628{col 71}{space 3} .1064084
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.2116743{col 30}{space 2} .0236786{col 41}{space 1}   -8.94{col 50}{space 3}0.000{col 58}{space 4}-.2580835{col 71}{space 3}-.1652652
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.056151{col 30}{space 2} .0848308{col 41}{space 1}   36.03{col 50}{space 3}0.000{col 58}{space 4} 2.889886{col 71}{space 3} 3.222417
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .67330789
         {txt}sigma_e {c |} {res} 1.0645743
             {txt}rho {c |} {res} .28572156{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,604
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,401

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0362                                         {txt}min = {res}         4
{txt}     between = {res}0.5197                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.3124                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}22{txt})     =  {res}  2116.59
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,401} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1186661{col 30}{space 2} .0163782{col 41}{space 1}    7.25{col 50}{space 3}0.000{col 58}{space 4} .0865655{col 71}{space 3} .1507668
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} -.010153{col 30}{space 2} .0104701{col 41}{space 1}   -0.97{col 50}{space 3}0.332{col 58}{space 4}-.0306741{col 71}{space 3} .0103681
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1948817{col 30}{space 2} .0909683{col 41}{space 1}   -2.14{col 50}{space 3}0.032{col 58}{space 4}-.3731762{col 71}{space 3}-.0165871
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0012495{col 30}{space 2} .0016453{col 41}{space 1}   -0.76{col 50}{space 3}0.448{col 58}{space 4}-.0044743{col 71}{space 3} .0019753
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1426317{col 30}{space 2} .0550988{col 41}{space 1}   -2.59{col 50}{space 3}0.010{col 58}{space 4}-.2506233{col 71}{space 3}-.0346401
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2536194{col 30}{space 2} .0553974{col 41}{space 1}    4.58{col 50}{space 3}0.000{col 58}{space 4} .1450426{col 71}{space 3} .3621963
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2374174{col 30}{space 2} .1603145{col 41}{space 1}    1.48{col 50}{space 3}0.139{col 58}{space 4}-.0767932{col 71}{space 3}  .551628
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1566744{col 30}{space 2} .0620513{col 41}{space 1}    2.52{col 50}{space 3}0.012{col 58}{space 4} .0350561{col 71}{space 3} .2782928
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4806294{col 30}{space 2} .1045356{col 41}{space 1}    4.60{col 50}{space 3}0.000{col 58}{space 4} .2757434{col 71}{space 3} .6855154
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1504033{col 30}{space 2} .0656532{col 41}{space 1}    2.29{col 50}{space 3}0.022{col 58}{space 4} .0217254{col 71}{space 3} .2790812
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2596149{col 30}{space 2} .0474542{col 41}{space 1}    5.47{col 50}{space 3}0.000{col 58}{space 4} .1666064{col 71}{space 3} .3526234
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1804891{col 30}{space 2} .0405231{col 41}{space 1}   -4.45{col 50}{space 3}0.000{col 58}{space 4} -.259913{col 71}{space 3}-.1010653
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0095032{col 30}{space 2} .0314002{col 41}{space 1}    0.30{col 50}{space 3}0.762{col 58}{space 4}-.0520401{col 71}{space 3} .0710465
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0408542{col 30}{space 2} .0562717{col 41}{space 1}    0.73{col 50}{space 3}0.468{col 58}{space 4}-.0694363{col 71}{space 3} .1511446
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1216177{col 30}{space 2}  .305902{col 41}{space 1}    0.40{col 50}{space 3}0.691{col 58}{space 4}-.4779392{col 71}{space 3} .7211745
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .735109{col 30}{space 2} .1053409{col 41}{space 1}    6.98{col 50}{space 3}0.000{col 58}{space 4} .5286447{col 71}{space 3} .9415733
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8036584{col 30}{space 2} .1466937{col 41}{space 1}    5.48{col 50}{space 3}0.000{col 58}{space 4}  .516144{col 71}{space 3} 1.091173
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4673223{col 30}{space 2} .1024907{col 41}{space 1}    4.56{col 50}{space 3}0.000{col 58}{space 4} .2664443{col 71}{space 3} .6682003
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3795386{col 30}{space 2} .0973342{col 41}{space 1}    3.90{col 50}{space 3}0.000{col 58}{space 4} .1887672{col 71}{space 3} .5703101
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0411007{col 30}{space 2} .0278909{col 41}{space 1}   -1.47{col 50}{space 3}0.141{col 58}{space 4}-.0957659{col 71}{space 3} .0135644
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .1409768{col 30}{space 2} .0493627{col 41}{space 1}    2.86{col 50}{space 3}0.004{col 58}{space 4} .0442277{col 71}{space 3} .2377259
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0833442{col 30}{space 2} .0421024{col 41}{space 1}    1.98{col 50}{space 3}0.048{col 58}{space 4}  .000825{col 71}{space 3} .1658633
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.917578{col 30}{space 2} .1383813{col 41}{space 1}   35.54{col 50}{space 3}0.000{col 58}{space 4} 4.646356{col 71}{space 3} 5.188801
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .63915826
         {txt}sigma_e {c |} {res} 1.2896187
             {txt}rho {c |} {res} .19719803{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,954
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,977

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0408                                         {txt}min = {res}         2
{txt}     between = {res}0.2822                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.1975                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}21{txt})     =  {res}  1330.25
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,977} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2462104{col 30}{space 2} .0346958{col 41}{space 1}    7.10{col 50}{space 3}0.000{col 58}{space 4} .1782079{col 71}{space 3} .3142128
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0082681{col 30}{space 2} .0069525{col 41}{space 1}    1.19{col 50}{space 3}0.234{col 58}{space 4}-.0053585{col 71}{space 3} .0218947
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0211012{col 30}{space 2} .1077814{col 41}{space 1}   -0.20{col 50}{space 3}0.845{col 58}{space 4}-.2323489{col 71}{space 3} .1901464
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0026419{col 30}{space 2} .0015314{col 41}{space 1}    1.73{col 50}{space 3}0.085{col 58}{space 4}-.0003596{col 71}{space 3} .0056434
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0987903{col 30}{space 2} .0626012{col 41}{space 1}    1.58{col 50}{space 3}0.115{col 58}{space 4}-.0239059{col 71}{space 3} .2214864
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3020967{col 30}{space 2} .0479813{col 41}{space 1}    6.30{col 50}{space 3}0.000{col 58}{space 4} .2080551{col 71}{space 3} .3961383
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2477165{col 30}{space 2} .0962287{col 41}{space 1}    2.57{col 50}{space 3}0.010{col 58}{space 4} .0591116{col 71}{space 3} .4363213
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1106006{col 30}{space 2} .0748353{col 41}{space 1}    1.48{col 50}{space 3}0.139{col 58}{space 4}-.0360739{col 71}{space 3} .2572751
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2434622{col 30}{space 2} .1061574{col 41}{space 1}    2.29{col 50}{space 3}0.022{col 58}{space 4} .0353976{col 71}{space 3} .4515269
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2157337{col 30}{space 2} .0839075{col 41}{space 1}    2.57{col 50}{space 3}0.010{col 58}{space 4}  .051278{col 71}{space 3} .3801894
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1797007{col 30}{space 2}  .065516{col 41}{space 1}   -2.74{col 50}{space 3}0.006{col 58}{space 4}-.3081097{col 71}{space 3}-.0512916
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1273733{col 30}{space 2}  .048156{col 41}{space 1}   -2.65{col 50}{space 3}0.008{col 58}{space 4}-.2217574{col 71}{space 3}-.0329892
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0010485{col 30}{space 2} .0017863{col 41}{space 1}   -0.59{col 50}{space 3}0.557{col 58}{space 4}-.0045496{col 71}{space 3} .0024525
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1342488{col 30}{space 2} .2347647{col 41}{space 1}    0.57{col 50}{space 3}0.567{col 58}{space 4}-.3258815{col 71}{space 3}  .594379
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1545688{col 30}{space 2} .1255641{col 41}{space 1}    1.23{col 50}{space 3}0.218{col 58}{space 4}-.0915324{col 71}{space 3} .4006699
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3911212{col 30}{space 2} .0974228{col 41}{space 1}    4.01{col 50}{space 3}0.000{col 58}{space 4} .2001759{col 71}{space 3} .5820665
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .551968{col 30}{space 2} .1295655{col 41}{space 1}    4.26{col 50}{space 3}0.000{col 58}{space 4} .2980243{col 71}{space 3} .8059118
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2260792{col 30}{space 2} .1102323{col 41}{space 1}    2.05{col 50}{space 3}0.040{col 58}{space 4} .0100279{col 71}{space 3} .4421306
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .5109026{col 30}{space 2} .0856466{col 41}{space 1}    5.97{col 50}{space 3}0.000{col 58}{space 4} .3430382{col 71}{space 3} .6787669
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2420637{col 30}{space 2} .0405313{col 41}{space 1}   -5.97{col 50}{space 3}0.000{col 58}{space 4}-.3215036{col 71}{space 3}-.1626239
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2775123{col 30}{space 2} .0386399{col 41}{space 1}    7.18{col 50}{space 3}0.000{col 58}{space 4} .2017794{col 71}{space 3} .3532451
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.440172{col 30}{space 2} .1248176{col 41}{space 1}   35.57{col 50}{space 3}0.000{col 58}{space 4} 4.195534{col 71}{space 3}  4.68481
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .60782393
         {txt}sigma_e {c |} {res} 1.3703359
             {txt}rho {c |} {res} .16439941{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,812
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,203

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0696                                         {txt}min = {res}         4
{txt}     between = {res}0.4044                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.2551                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1148.78
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,203} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0772565{col 30}{space 2} .0234437{col 41}{space 1}    3.30{col 50}{space 3}0.001{col 58}{space 4} .0313076{col 71}{space 3} .1232053
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0049385{col 30}{space 2} .0082601{col 41}{space 1}   -0.60{col 50}{space 3}0.550{col 58}{space 4}-.0211279{col 71}{space 3}  .011251
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0780622{col 30}{space 2} .0972277{col 41}{space 1}    0.80{col 50}{space 3}0.422{col 58}{space 4}-.1125006{col 71}{space 3}  .268625
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0066077{col 30}{space 2} .0018659{col 41}{space 1}    3.54{col 50}{space 3}0.000{col 58}{space 4} .0029506{col 71}{space 3} .0102649
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .081798{col 30}{space 2} .0687277{col 41}{space 1}    1.19{col 50}{space 3}0.234{col 58}{space 4}-.0529058{col 71}{space 3} .2165018
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0445503{col 30}{space 2} .0502785{col 41}{space 1}    0.89{col 50}{space 3}0.376{col 58}{space 4}-.0539938{col 71}{space 3} .1430944
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1083152{col 30}{space 2} .0652137{col 41}{space 1}    1.66{col 50}{space 3}0.097{col 58}{space 4}-.0195014{col 71}{space 3} .2361317
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1777471{col 30}{space 2} .0652817{col 41}{space 1}    2.72{col 50}{space 3}0.006{col 58}{space 4} .0497973{col 71}{space 3} .3056969
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1198799{col 30}{space 2} .0809097{col 41}{space 1}    1.48{col 50}{space 3}0.138{col 58}{space 4}-.0387001{col 71}{space 3} .2784599
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2771227{col 30}{space 2} .0815418{col 41}{space 1}    3.40{col 50}{space 3}0.001{col 58}{space 4} .1173037{col 71}{space 3} .4369416
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2638007{col 30}{space 2} .0609756{col 41}{space 1}    4.33{col 50}{space 3}0.000{col 58}{space 4} .1442907{col 71}{space 3} .3833107
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0113701{col 30}{space 2}  .089303{col 41}{space 1}    0.13{col 50}{space 3}0.899{col 58}{space 4}-.1636606{col 71}{space 3} .1864008
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0048255{col 30}{space 2} .0129025{col 41}{space 1}   -0.37{col 50}{space 3}0.708{col 58}{space 4} -.030114{col 71}{space 3} .0204631
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}   .14258{col 30}{space 2} .1155921{col 41}{space 1}    1.23{col 50}{space 3}0.217{col 58}{space 4}-.0839763{col 71}{space 3} .3691363
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.2608265{col 30}{space 2} .1089777{col 41}{space 1}   -2.39{col 50}{space 3}0.017{col 58}{space 4} -.474419{col 71}{space 3}-.0472341
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  1.13946{col 30}{space 2} .1291636{col 41}{space 1}    8.82{col 50}{space 3}0.000{col 58}{space 4} .8863038{col 71}{space 3} 1.392616
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .796432{col 30}{space 2} .1208415{col 41}{space 1}    6.59{col 50}{space 3}0.000{col 58}{space 4}  .559587{col 71}{space 3} 1.033277
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1485312{col 30}{space 2} .1302843{col 41}{space 1}    1.14{col 50}{space 3}0.254{col 58}{space 4}-.1068213{col 71}{space 3} .4038837
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0748144{col 30}{space 2} .1017302{col 41}{space 1}   -0.74{col 50}{space 3}0.462{col 58}{space 4} -.274202{col 71}{space 3} .1245732
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0537406{col 30}{space 2} .0382768{col 41}{space 1}   -1.40{col 50}{space 3}0.160{col 58}{space 4}-.1287617{col 71}{space 3} .0212805
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.6354287{col 30}{space 2} .0566514{col 41}{space 1}  -11.22{col 50}{space 3}0.000{col 58}{space 4}-.7464634{col 71}{space 3}-.5243939
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.4753477{col 30}{space 2} .0544434{col 41}{space 1}   -8.73{col 50}{space 3}0.000{col 58}{space 4}-.5820547{col 71}{space 3}-.3686407
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3636094{col 30}{space 2} .0518128{col 41}{space 1}   -7.02{col 50}{space 3}0.000{col 58}{space 4}-.4651606{col 71}{space 3}-.2620582
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.300944{col 30}{space 2}  .165953{col 41}{space 1}   25.92{col 50}{space 3}0.000{col 58}{space 4} 3.975682{col 71}{space 3} 4.626206
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .7264299
         {txt}sigma_e {c |} {res} 1.2511251
             {txt}rho {c |} {res} .25212458{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     1,585
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}       317

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0440                                         {txt}min = {res}         5
{txt}     between = {res}0.4595                                         {txt}avg = {res}       5.0
{txt}     overall = {res}0.2710                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}23{txt})     =  {res}   362.64
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:317} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1648247{col 30}{space 2} .0302213{col 41}{space 1}    5.45{col 50}{space 3}0.000{col 58}{space 4}  .105592{col 71}{space 3} .2240575
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} -.046104{col 30}{space 2} .0185301{col 41}{space 1}   -2.49{col 50}{space 3}0.013{col 58}{space 4}-.0824222{col 71}{space 3}-.0097857
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1226306{col 30}{space 2} .1943072{col 41}{space 1}    0.63{col 50}{space 3}0.528{col 58}{space 4}-.2582045{col 71}{space 3} .5034658
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0084777{col 30}{space 2} .0037519{col 41}{space 1}   -2.26{col 50}{space 3}0.024{col 58}{space 4}-.0158312{col 71}{space 3}-.0011241
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2180765{col 30}{space 2} .1187846{col 41}{space 1}    1.84{col 50}{space 3}0.066{col 58}{space 4} -.014737{col 71}{space 3} .4508901
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0961355{col 30}{space 2} .1213568{col 41}{space 1}    0.79{col 50}{space 3}0.428{col 58}{space 4}-.1417194{col 71}{space 3} .3339904
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3041021{col 30}{space 2} .1421985{col 41}{space 1}    2.14{col 50}{space 3}0.032{col 58}{space 4} .0253982{col 71}{space 3}  .582806
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1443793{col 30}{space 2}  .102829{col 41}{space 1}    1.40{col 50}{space 3}0.160{col 58}{space 4}-.0571619{col 71}{space 3} .3459205
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1069979{col 30}{space 2} .1097482{col 41}{space 1}    0.97{col 50}{space 3}0.330{col 58}{space 4}-.1081046{col 71}{space 3} .3221004
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1087959{col 30}{space 2} .0792676{col 41}{space 1}    1.37{col 50}{space 3}0.170{col 58}{space 4}-.0465657{col 71}{space 3} .2641575
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3011132{col 30}{space 2} .0886196{col 41}{space 1}    3.40{col 50}{space 3}0.001{col 58}{space 4} .1274219{col 71}{space 3} .4748044
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1452239{col 30}{space 2} .0944994{col 41}{space 1}   -1.54{col 50}{space 3}0.124{col 58}{space 4}-.3304393{col 71}{space 3} .0399914
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0072251{col 30}{space 2} .0147748{col 41}{space 1}   -0.49{col 50}{space 3}0.625{col 58}{space 4}-.0361831{col 71}{space 3} .0217329
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0509507{col 30}{space 2} .0849449{col 41}{space 1}   -0.60{col 50}{space 3}0.549{col 58}{space 4}-.2174396{col 71}{space 3} .1155383
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2726041{col 30}{space 2} .3167451{col 41}{space 1}    0.86{col 50}{space 3}0.389{col 58}{space 4}-.3482049{col 71}{space 3}  .893413
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} 1.121389{col 30}{space 2} .2246503{col 41}{space 1}    4.99{col 50}{space 3}0.000{col 58}{space 4} .6810826{col 71}{space 3} 1.561696
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.164823{col 30}{space 2} .2253054{col 41}{space 1}    5.17{col 50}{space 3}0.000{col 58}{space 4} .7232328{col 71}{space 3} 1.606414
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2206696{col 30}{space 2} .1893146{col 41}{space 1}   -1.17{col 50}{space 3}0.244{col 58}{space 4}-.5917195{col 71}{space 3} .1503802
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.1914531{col 30}{space 2} .1998388{col 41}{space 1}   -0.96{col 50}{space 3}0.338{col 58}{space 4}-.5831299{col 71}{space 3} .2002238
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0595825{col 30}{space 2}  .051726{col 41}{space 1}   -1.15{col 50}{space 3}0.249{col 58}{space 4}-.1609637{col 71}{space 3} .0417987
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.0641729{col 30}{space 2} .0989855{col 41}{space 1}   -0.65{col 50}{space 3}0.517{col 58}{space 4}-.2581809{col 71}{space 3} .1298351
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0128783{col 30}{space 2} .0828823{col 41}{space 1}   -0.16{col 50}{space 3}0.877{col 58}{space 4}-.1753246{col 71}{space 3}  .149568
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .1279383{col 30}{space 2} .0827227{col 41}{space 1}    1.55{col 50}{space 3}0.122{col 58}{space 4}-.0341952{col 71}{space 3} .2900718
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.776133{col 30}{space 2} .3274591{col 41}{space 1}   14.59{col 50}{space 3}0.000{col 58}{space 4} 4.134325{col 71}{space 3} 5.417941
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .71774373
         {txt}sigma_e {c |} {res} 1.2084667
             {txt}rho {c |} {res} .26076617{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,805
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,115

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0728                                         {txt}min = {res}         7
{txt}     between = {res}0.3429                                         {txt}avg = {res}       7.0
{txt}     overall = {res}0.1884                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}25{txt})     =  {res}  1123.18
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,115} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0931173{col 30}{space 2} .0140695{col 41}{space 1}    6.62{col 50}{space 3}0.000{col 58}{space 4} .0655417{col 71}{space 3} .1206929
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0051279{col 30}{space 2} .0081545{col 41}{space 1}   -0.63{col 50}{space 3}0.529{col 58}{space 4}-.0211105{col 71}{space 3} .0108548
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1524215{col 30}{space 2} .0850124{col 41}{space 1}    1.79{col 50}{space 3}0.073{col 58}{space 4}-.0141998{col 71}{space 3} .3190427
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} 2.40e-06{col 30}{space 2} .0017912{col 41}{space 1}    0.00{col 50}{space 3}0.999{col 58}{space 4}-.0035082{col 71}{space 3}  .003513
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0194589{col 30}{space 2} .0518099{col 41}{space 1}    0.38{col 50}{space 3}0.707{col 58}{space 4}-.0820866{col 71}{space 3} .1210045
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2470626{col 30}{space 2} .0487245{col 41}{space 1}    5.07{col 50}{space 3}0.000{col 58}{space 4} .1515642{col 71}{space 3} .3425609
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1518173{col 30}{space 2} .0666783{col 41}{space 1}    2.28{col 50}{space 3}0.023{col 58}{space 4} .0211302{col 71}{space 3} .2825044
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2890934{col 30}{space 2} .0481648{col 41}{space 1}    6.00{col 50}{space 3}0.000{col 58}{space 4} .1946922{col 71}{space 3} .3834946
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3612839{col 30}{space 2}  .048076{col 41}{space 1}    7.51{col 50}{space 3}0.000{col 58}{space 4} .2670567{col 71}{space 3} .4555112
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0743029{col 30}{space 2} .0395922{col 41}{space 1}    1.88{col 50}{space 3}0.061{col 58}{space 4}-.0032963{col 71}{space 3} .1519021
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1788176{col 30}{space 2}  .040952{col 41}{space 1}    4.37{col 50}{space 3}0.000{col 58}{space 4} .0985531{col 71}{space 3} .2590821
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0010177{col 30}{space 2} .0344328{col 41}{space 1}    0.03{col 50}{space 3}0.976{col 58}{space 4}-.0664694{col 71}{space 3} .0685048
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0014094{col 30}{space 2} .0013769{col 41}{space 1}    1.02{col 50}{space 3}0.306{col 58}{space 4}-.0012893{col 71}{space 3} .0041082
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0404014{col 30}{space 2} .0395603{col 41}{space 1}   -1.02{col 50}{space 3}0.307{col 58}{space 4}-.1179381{col 71}{space 3} .0371353
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .179306{col 30}{space 2} .1331795{col 41}{space 1}    1.35{col 50}{space 3}0.178{col 58}{space 4} -.081721{col 71}{space 3}  .440333
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3467075{col 30}{space 2} .1073867{col 41}{space 1}    3.23{col 50}{space 3}0.001{col 58}{space 4} .1362334{col 71}{space 3} .5571817
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6455224{col 30}{space 2} .1270546{col 41}{space 1}    5.08{col 50}{space 3}0.000{col 58}{space 4} .3964999{col 71}{space 3} .8945448
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1564873{col 30}{space 2} .1001065{col 41}{space 1}    1.56{col 50}{space 3}0.118{col 58}{space 4}-.0397179{col 71}{space 3} .3526926
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3199249{col 30}{space 2} .0895816{col 41}{space 1}    3.57{col 50}{space 3}0.000{col 58}{space 4} .1443481{col 71}{space 3} .4955016
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0114474{col 30}{space 2} .0257771{col 41}{space 1}    0.44{col 50}{space 3}0.657{col 58}{space 4}-.0390749{col 71}{space 3} .0619696
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} -.184646{col 30}{space 2} .0482837{col 41}{space 1}   -3.82{col 50}{space 3}0.000{col 58}{space 4}-.2792803{col 71}{space 3}-.0900118
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.1107628{col 30}{space 2} .0460806{col 41}{space 1}   -2.40{col 50}{space 3}0.016{col 58}{space 4} -.201079{col 71}{space 3}-.0204466
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3936868{col 30}{space 2} .0456925{col 41}{space 1}    8.62{col 50}{space 3}0.000{col 58}{space 4} .3041311{col 71}{space 3} .4832425
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1253153{col 30}{space 2} .0461418{col 41}{space 1}    2.72{col 50}{space 3}0.007{col 58}{space 4} .0348791{col 71}{space 3} .2157516
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .3745043{col 30}{space 2} .0447926{col 41}{space 1}    8.36{col 50}{space 3}0.000{col 58}{space 4} .2867125{col 71}{space 3} .4622961
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.945697{col 30}{space 2} .1609959{col 41}{space 1}   24.51{col 50}{space 3}0.000{col 58}{space 4} 3.630151{col 71}{space 3} 4.261244
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .68356284
         {txt}sigma_e {c |} {res} 1.2407017
             {txt}rho {c |} {res} .23286078{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S12_balance.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean _cons)
{res}{txt}(note: file S12_balance.rtf not found)
(output written to {browse  `"S12_balance.rtf"'})

{com}. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. ******************************************************************************** 
. *                                  S13_S14                                     *
. ********************************************************************************
. preserve
{txt}
{com}. eststo clear
{txt}
{com}. drop if hdd9_own==.|hdd9_purchase==.
{txt}(2,055 observations deleted)

{com}. drop  pdd9_mean no_species_mean hhsize_mean dependent_share_mean head_age_mean female_head_mean head_read_mean motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean weather_shock_mean plot_area_mean other_crop_mean
{txt}
{com}. foreach x of varlist pdd9 hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. 
. eststo clear
{txt}
{com}. xtreg hdd9_own  pdd9   $xlist  pdd9_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    33,152
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    10,109

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0772                                         {txt}min = {res}         1
{txt}     between = {res}0.6222                                         {txt}avg = {res}       3.3
{txt}     overall = {res}0.4765                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 23808.57
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:10,109} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2042727{col 30}{space 2} .0074233{col 41}{space 1}   27.52{col 50}{space 3}0.000{col 58}{space 4} .1897234{col 71}{space 3} .2188221
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0110427{col 30}{space 2} .0028694{col 41}{space 1}    3.85{col 50}{space 3}0.000{col 58}{space 4} .0054187{col 71}{space 3} .0166666
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0123459{col 30}{space 2} .0311885{col 41}{space 1}   -0.40{col 50}{space 3}0.692{col 58}{space 4}-.0734742{col 71}{space 3} .0487824
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0017867{col 30}{space 2} .0005342{col 41}{space 1}    3.34{col 50}{space 3}0.001{col 58}{space 4} .0007396{col 71}{space 3} .0028338
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0784496{col 30}{space 2} .0195431{col 41}{space 1}   -4.01{col 50}{space 3}0.000{col 58}{space 4}-.1167533{col 71}{space 3}-.0401458
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0846672{col 30}{space 2} .0166524{col 41}{space 1}    5.08{col 50}{space 3}0.000{col 58}{space 4}  .052029{col 71}{space 3} .1173053
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0370217{col 30}{space 2} .0304767{col 41}{space 1}    1.21{col 50}{space 3}0.224{col 58}{space 4}-.0227115{col 71}{space 3} .0967549
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0288749{col 30}{space 2}  .020588{col 41}{space 1}    1.40{col 50}{space 3}0.161{col 58}{space 4}-.0114769{col 71}{space 3} .0692266
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0012338{col 30}{space 2} .0257019{col 41}{space 1}   -0.05{col 50}{space 3}0.962{col 58}{space 4}-.0516087{col 71}{space 3} .0491411
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0628206{col 30}{space 2}  .022064{col 41}{space 1}   -2.85{col 50}{space 3}0.004{col 58}{space 4}-.1060651{col 71}{space 3} -.019576
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0037831{col 30}{space 2} .0203244{col 41}{space 1}    0.19{col 50}{space 3}0.852{col 58}{space 4} -.036052{col 71}{space 3} .0436182
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0443262{col 30}{space 2} .0161764{col 41}{space 1}   -2.74{col 50}{space 3}0.006{col 58}{space 4}-.0760313{col 71}{space 3} -.012621
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0022958{col 30}{space 2} .0010742{col 41}{space 1}    2.14{col 50}{space 3}0.033{col 58}{space 4} .0001904{col 71}{space 3} .0044013
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0906989{col 30}{space 2} .0202046{col 41}{space 1}    4.49{col 50}{space 3}0.000{col 58}{space 4} .0510986{col 71}{space 3} .1302992
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1094629{col 30}{space 2} .0444244{col 41}{space 1}    2.46{col 50}{space 3}0.014{col 58}{space 4} .0223926{col 71}{space 3} .1965332
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0036355{col 30}{space 2} .0320585{col 41}{space 1}    0.11{col 50}{space 3}0.910{col 58}{space 4} -.059198{col 71}{space 3} .0664691
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.2125401{col 30}{space 2} .0362202{col 41}{space 1}   -5.87{col 50}{space 3}0.000{col 58}{space 4}-.2835305{col 71}{space 3}-.1415497
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2054215{col 30}{space 2} .0345621{col 41}{space 1}   -5.94{col 50}{space 3}0.000{col 58}{space 4}-.2731619{col 71}{space 3}-.1376811
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2830134{col 30}{space 2} .0291686{col 41}{space 1}   -9.70{col 50}{space 3}0.000{col 58}{space 4}-.3401827{col 71}{space 3} -.225844
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2983164{col 30}{space 2} .0098697{col 41}{space 1}   30.23{col 50}{space 3}0.000{col 58}{space 4} .2789721{col 71}{space 3} .3176607
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2} .2792702{col 30}{space 2} .0335336{col 41}{space 1}    8.33{col 50}{space 3}0.000{col 58}{space 4} .2135456{col 71}{space 3} .3449947
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-.2109347{col 30}{space 2} .0305258{col 41}{space 1}   -6.91{col 50}{space 3}0.000{col 58}{space 4}-.2707643{col 71}{space 3}-.1511052
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2} 1.092042{col 30}{space 2} .0367227{col 41}{space 1}   29.74{col 50}{space 3}0.000{col 58}{space 4} 1.020067{col 71}{space 3} 1.164017
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}  .589606{col 30}{space 2} .0516411{col 41}{space 1}   11.42{col 50}{space 3}0.000{col 58}{space 4} .4883912{col 71}{space 3} .6908207
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .7573502{col 30}{space 2}  .036728{col 41}{space 1}   20.62{col 50}{space 3}0.000{col 58}{space 4} .6853646{col 71}{space 3} .8293358
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2091301{col 30}{space 2} .0828997{col 41}{space 1}   -2.52{col 50}{space 3}0.012{col 58}{space 4}-.3716105{col 71}{space 3}-.0466497
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0596312{col 30}{space 2} .0753363{col 41}{space 1}   -0.79{col 50}{space 3}0.429{col 58}{space 4}-.2072876{col 71}{space 3} .0880252
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .1416198{col 30}{space 2} .0768118{col 41}{space 1}    1.84{col 50}{space 3}0.065{col 58}{space 4}-.0089286{col 71}{space 3} .2921682
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0793932{col 30}{space 2} .0749875{col 41}{space 1}    1.06{col 50}{space 3}0.290{col 58}{space 4}-.0675796{col 71}{space 3}  .226366
{txt}{space 11}2013  {c |}{col 18}{res}{space 2}-.0057813{col 30}{space 2} .0770598{col 41}{space 1}   -0.08{col 50}{space 3}0.940{col 58}{space 4}-.1568158{col 71}{space 3} .1452531
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.2277194{col 30}{space 2} .0781291{col 41}{space 1}   -2.91{col 50}{space 3}0.004{col 58}{space 4}-.3808497{col 71}{space 3}-.0745891
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .0458349{col 30}{space 2} .0767388{col 41}{space 1}    0.60{col 50}{space 3}0.550{col 58}{space 4}-.1045704{col 71}{space 3} .1962403
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.4434691{col 30}{space 2} .0817192{col 41}{space 1}   -5.43{col 50}{space 3}0.000{col 58}{space 4}-.6036359{col 71}{space 3}-.2833023
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .3537478{col 30}{space 2} .0788123{col 41}{space 1}    4.49{col 50}{space 3}0.000{col 58}{space 4} .1992785{col 71}{space 3}  .508217
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.2159855{col 30}{space 2} .0781305{col 41}{space 1}   -2.76{col 50}{space 3}0.006{col 58}{space 4}-.3691186{col 71}{space 3}-.0628525
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} .0176601{col 30}{space 2}  .087441{col 41}{space 1}    0.20{col 50}{space 3}0.840{col 58}{space 4}-.1537212{col 71}{space 3} .1890414
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .40618447
         {txt}sigma_e {c |} {res}  1.034094
             {txt}rho {c |} {res}  .1336636{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,449
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,096

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0299                                         {txt}min = {res}         1
{txt}     between = {res}0.4035                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.3196                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}21{txt})     =  {res}  2688.97
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,096} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0751365{col 30}{space 2}  .011607{col 41}{space 1}    6.47{col 50}{space 3}0.000{col 58}{space 4} .0523872{col 71}{space 3} .0978858
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0369333{col 30}{space 2} .0073154{col 41}{space 1}    5.05{col 50}{space 3}0.000{col 58}{space 4} .0225953{col 71}{space 3} .0512713
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .009612{col 30}{space 2} .0585794{col 41}{space 1}    0.16{col 50}{space 3}0.870{col 58}{space 4}-.1052015{col 71}{space 3} .1244254
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0025867{col 30}{space 2} .0009672{col 41}{space 1}    2.67{col 50}{space 3}0.007{col 58}{space 4} .0006909{col 71}{space 3} .0044824
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0629277{col 30}{space 2} .0358252{col 41}{space 1}   -1.76{col 50}{space 3}0.079{col 58}{space 4}-.1331437{col 71}{space 3} .0072883
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0924338{col 30}{space 2} .0302371{col 41}{space 1}    3.06{col 50}{space 3}0.002{col 58}{space 4} .0331701{col 71}{space 3} .1516974
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2436247{col 30}{space 2} .1741653{col 41}{space 1}   -1.40{col 50}{space 3}0.162{col 58}{space 4}-.5849825{col 71}{space 3} .0977331
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0322644{col 30}{space 2} .0390302{col 41}{space 1}    0.83{col 50}{space 3}0.408{col 58}{space 4}-.0442334{col 71}{space 3} .1087621
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.1618227{col 30}{space 2} .0448092{col 41}{space 1}   -3.61{col 50}{space 3}0.000{col 58}{space 4}-.2496472{col 71}{space 3}-.0739982
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0018099{col 30}{space 2} .0655798{col 41}{space 1}   -0.03{col 50}{space 3}0.978{col 58}{space 4}-.1303439{col 71}{space 3} .1267242
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0227433{col 30}{space 2} .0515276{col 41}{space 1}   -0.44{col 50}{space 3}0.659{col 58}{space 4}-.1237356{col 71}{space 3} .0782489
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1836471{col 30}{space 2} .0289511{col 41}{space 1}   -6.34{col 50}{space 3}0.000{col 58}{space 4}-.2403901{col 71}{space 3} -.126904
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0173978{col 30}{space 2}  .006869{col 41}{space 1}    2.53{col 50}{space 3}0.011{col 58}{space 4} .0039347{col 71}{space 3} .0308608
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0273309{col 30}{space 2} .0291547{col 41}{space 1}   -0.94{col 50}{space 3}0.349{col 58}{space 4}-.0844731{col 71}{space 3} .0298113
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .3042009{col 30}{space 2}  .293882{col 41}{space 1}    1.04{col 50}{space 3}0.301{col 58}{space 4}-.2717973{col 71}{space 3}  .880199
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0378754{col 30}{space 2} .0561706{col 41}{space 1}   -0.67{col 50}{space 3}0.500{col 58}{space 4}-.1479678{col 71}{space 3}  .072217
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.2284559{col 30}{space 2} .0638872{col 41}{space 1}   -3.58{col 50}{space 3}0.000{col 58}{space 4}-.3536724{col 71}{space 3}-.1032393
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.3841741{col 30}{space 2} .1088639{col 41}{space 1}   -3.53{col 50}{space 3}0.000{col 58}{space 4}-.5975434{col 71}{space 3}-.1708048
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} -.221592{col 30}{space 2} .0651948{col 41}{space 1}   -3.40{col 50}{space 3}0.001{col 58}{space 4}-.3493714{col 71}{space 3}-.0938125
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2643956{col 30}{space 2} .0150206{col 41}{space 1}   17.60{col 50}{space 3}0.000{col 58}{space 4} .2349557{col 71}{space 3} .2938354
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1618934{col 30}{space 2} .0226012{col 41}{space 1}   -7.16{col 50}{space 3}0.000{col 58}{space 4}-.2061909{col 71}{space 3} -.117596
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .4709687{col 30}{space 2} .0706718{col 41}{space 1}    6.66{col 50}{space 3}0.000{col 58}{space 4} .3324544{col 71}{space 3} .6094829
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .59403277
         {txt}sigma_e {c |} {res} .87771353
             {txt}rho {c |} {res} .31415363{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,598
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,401

{txt}R-sq:                                           Obs per group:
     within  = {res}0.1547                                         {txt}min = {res}         3
{txt}     between = {res}0.6448                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.4393                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}22{txt})     =  {res}  4394.14
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,401} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .3111439{col 30}{space 2}  .016092{col 41}{space 1}   19.34{col 50}{space 3}0.000{col 58}{space 4} .2796042{col 71}{space 3} .3426836
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0114765{col 30}{space 2} .0092452{col 41}{space 1}   -1.24{col 50}{space 3}0.214{col 58}{space 4}-.0295967{col 71}{space 3} .0066436
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0496842{col 30}{space 2} .0766652{col 41}{space 1}    0.65{col 50}{space 3}0.517{col 58}{space 4}-.1005768{col 71}{space 3} .1999452
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0023577{col 30}{space 2} .0014147{col 41}{space 1}    1.67{col 50}{space 3}0.096{col 58}{space 4}-.0004149{col 71}{space 3} .0051304
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} -.081478{col 30}{space 2} .0451983{col 41}{space 1}   -1.80{col 50}{space 3}0.071{col 58}{space 4}-.1700651{col 71}{space 3} .0071091
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0466782{col 30}{space 2} .0451326{col 41}{space 1}    1.03{col 50}{space 3}0.301{col 58}{space 4}-.0417801{col 71}{space 3} .1351365
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .420019{col 30}{space 2} .1434292{col 41}{space 1}    2.93{col 50}{space 3}0.003{col 58}{space 4} .1389029{col 71}{space 3}  .701135
{txt}{space 11}phone {c |}{col 18}{res}{space 2} -.009017{col 30}{space 2}  .050527{col 41}{space 1}   -0.18{col 50}{space 3}0.858{col 58}{space 4}-.1080481{col 71}{space 3} .0900142
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0026325{col 30}{space 2} .0826098{col 41}{space 1}    0.03{col 50}{space 3}0.975{col 58}{space 4}-.1592797{col 71}{space 3} .1645447
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0482755{col 30}{space 2} .0562008{col 41}{space 1}   -0.86{col 50}{space 3}0.390{col 58}{space 4}-.1584271{col 71}{space 3} .0618761
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0656034{col 30}{space 2} .0444438{col 41}{space 1}    1.48{col 50}{space 3}0.140{col 58}{space 4}-.0215048{col 71}{space 3} .1527117
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1356333{col 30}{space 2} .0355701{col 41}{space 1}   -3.81{col 50}{space 3}0.000{col 58}{space 4}-.2053494{col 71}{space 3}-.0659172
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .1385358{col 30}{space 2} .0321975{col 41}{space 1}    4.30{col 50}{space 3}0.000{col 58}{space 4} .0754298{col 71}{space 3} .2016417
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1632406{col 30}{space 2} .0503493{col 41}{space 1}    3.24{col 50}{space 3}0.001{col 58}{space 4} .0645578{col 71}{space 3} .2619235
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.4726263{col 30}{space 2} .2381466{col 41}{space 1}   -1.98{col 50}{space 3}0.047{col 58}{space 4}-.9393851{col 71}{space 3}-.0058674
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .010649{col 30}{space 2} .0850636{col 41}{space 1}    0.13{col 50}{space 3}0.900{col 58}{space 4}-.1560727{col 71}{space 3} .1773707
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.0721196{col 30}{space 2} .1068817{col 41}{space 1}   -0.67{col 50}{space 3}0.500{col 58}{space 4}-.2816038{col 71}{space 3} .1373647
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0252699{col 30}{space 2} .0861742{col 41}{space 1}    0.29{col 50}{space 3}0.769{col 58}{space 4}-.1436285{col 71}{space 3} .1941683
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2944318{col 30}{space 2}  .075094{col 41}{space 1}   -3.92{col 50}{space 3}0.000{col 58}{space 4}-.4416134{col 71}{space 3}-.1472502
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .3533004{col 30}{space 2} .0241429{col 41}{space 1}   14.63{col 50}{space 3}0.000{col 58}{space 4} .3059812{col 71}{space 3} .4006197
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .5708881{col 30}{space 2} .0419634{col 41}{space 1}   13.60{col 50}{space 3}0.000{col 58}{space 4} .4886413{col 71}{space 3} .6531348
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .2915429{col 30}{space 2} .0363306{col 41}{space 1}    8.02{col 50}{space 3}0.000{col 58}{space 4} .2203363{col 71}{space 3} .3627496
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.1232269{col 30}{space 2} .1157358{col 41}{space 1}   -1.06{col 50}{space 3}0.287{col 58}{space 4}-.3500648{col 71}{space 3} .1036111
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .47652069
         {txt}sigma_e {c |} {res} 1.0998083
             {txt}rho {c |} {res} .15805653{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,952
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,977

{txt}R-sq:                                           Obs per group:
     within  = {res}0.1588                                         {txt}min = {res}         1
{txt}     between = {res}0.5146                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.4096                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}21{txt})     =  {res}  4241.32
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,977} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1981438{col 30}{space 2} .0218775{col 41}{space 1}    9.06{col 50}{space 3}0.000{col 58}{space 4} .1552647{col 71}{space 3} .2410228
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0044327{col 30}{space 2} .0038789{col 41}{space 1}   -1.14{col 50}{space 3}0.253{col 58}{space 4}-.0120352{col 71}{space 3} .0031698
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0305667{col 30}{space 2} .0536198{col 41}{space 1}    0.57{col 50}{space 3}0.569{col 58}{space 4}-.0745261{col 71}{space 3} .1356595
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0012077{col 30}{space 2} .0008766{col 41}{space 1}   -1.38{col 50}{space 3}0.168{col 58}{space 4}-.0029259{col 71}{space 3} .0005104
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1470815{col 30}{space 2} .0285244{col 41}{space 1}   -5.16{col 50}{space 3}0.000{col 58}{space 4}-.2029883{col 71}{space 3}-.0911747
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0567204{col 30}{space 2} .0270011{col 41}{space 1}    2.10{col 50}{space 3}0.036{col 58}{space 4} .0037993{col 71}{space 3} .1096416
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0450647{col 30}{space 2} .0434922{col 41}{space 1}    1.04{col 50}{space 3}0.300{col 58}{space 4}-.0401784{col 71}{space 3} .1303078
{txt}{space 11}phone {c |}{col 18}{res}{space 2}-.0708295{col 30}{space 2} .0407175{col 41}{space 1}   -1.74{col 50}{space 3}0.082{col 58}{space 4}-.1506343{col 71}{space 3} .0089754
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1412094{col 30}{space 2} .0407518{col 41}{space 1}    3.47{col 50}{space 3}0.001{col 58}{space 4} .0613373{col 71}{space 3} .2210815
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0809753{col 30}{space 2} .0435704{col 41}{space 1}    1.86{col 50}{space 3}0.063{col 58}{space 4}-.0044212{col 71}{space 3} .1663717
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0142928{col 30}{space 2}  .037656{col 41}{space 1}   -0.38{col 50}{space 3}0.704{col 58}{space 4}-.0880972{col 71}{space 3} .0595117
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0073835{col 30}{space 2}  .030226{col 41}{space 1}   -0.24{col 50}{space 3}0.807{col 58}{space 4}-.0666254{col 71}{space 3} .0518583
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0022423{col 30}{space 2} .0012638{col 41}{space 1}    1.77{col 50}{space 3}0.076{col 58}{space 4}-.0002347{col 71}{space 3} .0047193
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2738188{col 30}{space 2} .1546281{col 41}{space 1}    1.77{col 50}{space 3}0.077{col 58}{space 4}-.0292467{col 71}{space 3} .5768844
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0938348{col 30}{space 2} .0562954{col 41}{space 1}   -1.67{col 50}{space 3}0.096{col 58}{space 4}-.2041719{col 71}{space 3} .0165022
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0925144{col 30}{space 2} .0540984{col 41}{space 1}   -1.71{col 50}{space 3}0.087{col 58}{space 4}-.1985454{col 71}{space 3} .0135166
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.3039958{col 30}{space 2} .0552061{col 41}{space 1}   -5.51{col 50}{space 3}0.000{col 58}{space 4}-.4121977{col 71}{space 3}-.1957939
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1226854{col 30}{space 2} .0519711{col 41}{space 1}   -2.36{col 50}{space 3}0.018{col 58}{space 4}-.2245468{col 71}{space 3} -.020824
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} -.043741{col 30}{space 2} .0486939{col 41}{space 1}   -0.90{col 50}{space 3}0.369{col 58}{space 4}-.1391793{col 71}{space 3} .0516973
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2329743{col 30}{space 2} .0237993{col 41}{space 1}    9.79{col 50}{space 3}0.000{col 58}{space 4} .1863285{col 71}{space 3}   .27962
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .3906533{col 30}{space 2} .0210986{col 41}{space 1}   18.52{col 50}{space 3}0.000{col 58}{space 4} .3493007{col 71}{space 3} .4320058
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0978135{col 30}{space 2} .0640464{col 41}{space 1}    1.53{col 50}{space 3}0.127{col 58}{space 4}-.0277151{col 71}{space 3} .2233422
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .33049355
         {txt}sigma_e {c |} {res} .76186721
             {txt}rho {c |} {res} .15837482{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,770
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,203

{txt}R-sq:                                           Obs per group:
     within  = {res}0.1247                                         {txt}min = {res}         3
{txt}     between = {res}0.6489                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.4224                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  3361.69
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,203} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2172382{col 30}{space 2} .0201227{col 41}{space 1}   10.80{col 50}{space 3}0.000{col 58}{space 4} .1777984{col 71}{space 3}  .256678
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0186024{col 30}{space 2}  .006066{col 41}{space 1}    3.07{col 50}{space 3}0.002{col 58}{space 4} .0067132{col 71}{space 3} .0304915
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1088597{col 30}{space 2} .0680808{col 41}{space 1}   -1.60{col 50}{space 3}0.110{col 58}{space 4}-.2422957{col 71}{space 3} .0245763
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.000282{col 30}{space 2}  .001159{col 41}{space 1}   -0.24{col 50}{space 3}0.808{col 58}{space 4}-.0025536{col 71}{space 3} .0019896
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0370782{col 30}{space 2} .0485845{col 41}{space 1}   -0.76{col 50}{space 3}0.445{col 58}{space 4}-.1323021{col 71}{space 3} .0581456
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}-.0329942{col 30}{space 2} .0383729{col 41}{space 1}   -0.86{col 50}{space 3}0.390{col 58}{space 4}-.1082037{col 71}{space 3} .0422153
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0295022{col 30}{space 2} .0452248{col 41}{space 1}   -0.65{col 50}{space 3}0.514{col 58}{space 4}-.1181411{col 71}{space 3} .0591367
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0653904{col 30}{space 2} .0456929{col 41}{space 1}    1.43{col 50}{space 3}0.152{col 58}{space 4} -.024166{col 71}{space 3} .1549469
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0662292{col 30}{space 2} .0607122{col 41}{space 1}   -1.09{col 50}{space 3}0.275{col 58}{space 4}-.1852228{col 71}{space 3} .0527645
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0596088{col 30}{space 2} .0515901{col 41}{space 1}    1.16{col 50}{space 3}0.248{col 58}{space 4} -.041506{col 71}{space 3} .1607236
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0408992{col 30}{space 2} .0474066{col 41}{space 1}    0.86{col 50}{space 3}0.388{col 58}{space 4} -.052016{col 71}{space 3} .1338144
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0063991{col 30}{space 2} .0655043{col 41}{space 1}    0.10{col 50}{space 3}0.922{col 58}{space 4}-.1219869{col 71}{space 3} .1347851
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0280572{col 30}{space 2} .0124157{col 41}{space 1}    2.26{col 50}{space 3}0.024{col 58}{space 4} .0037229{col 71}{space 3} .0523915
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0520905{col 30}{space 2} .0910978{col 41}{space 1}    0.57{col 50}{space 3}0.567{col 58}{space 4} -.126458{col 71}{space 3} .2306389
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1058481{col 30}{space 2} .0710893{col 41}{space 1}    1.49{col 50}{space 3}0.137{col 58}{space 4}-.0334843{col 71}{space 3} .2451806
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1184891{col 30}{space 2} .0848974{col 41}{space 1}    1.40{col 50}{space 3}0.163{col 58}{space 4}-.0479068{col 71}{space 3} .2848849
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.3355347{col 30}{space 2} .0815411{col 41}{space 1}   -4.11{col 50}{space 3}0.000{col 58}{space 4}-.4953524{col 71}{space 3}-.1757171
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.3358192{col 30}{space 2}  .077377{col 41}{space 1}   -4.34{col 50}{space 3}0.000{col 58}{space 4}-.4874753{col 71}{space 3}-.1841632
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.3093634{col 30}{space 2} .0697424{col 41}{space 1}   -4.44{col 50}{space 3}0.000{col 58}{space 4} -.446056{col 71}{space 3}-.1726709
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}  .230798{col 30}{space 2} .0259961{col 41}{space 1}    8.88{col 50}{space 3}0.000{col 58}{space 4} .1798466{col 71}{space 3} .2817494
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5741354{col 30}{space 2} .0440067{col 41}{space 1}  -13.05{col 50}{space 3}0.000{col 58}{space 4} -.660387{col 71}{space 3}-.4878838
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} -.354702{col 30}{space 2} .0408231{col 41}{space 1}   -8.69{col 50}{space 3}0.000{col 58}{space 4}-.4347138{col 71}{space 3}-.2746902
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.4034065{col 30}{space 2} .0412882{col 41}{space 1}   -9.77{col 50}{space 3}0.000{col 58}{space 4}  -.48433{col 71}{space 3} -.322483
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  .991113{col 30}{space 2} .1062471{col 41}{space 1}    9.33{col 50}{space 3}0.000{col 58}{space 4} .7828725{col 71}{space 3} 1.199353
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .35016151
         {txt}sigma_e {c |} {res} .92153951
             {txt}rho {c |} {res} .12616486{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     1,582
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}       317

{txt}R-sq:                                           Obs per group:
     within  = {res}0.1587                                         {txt}min = {res}         4
{txt}     between = {res}0.7019                                         {txt}avg = {res}       5.0
{txt}     overall = {res}0.4901                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1429.81
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:317} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .3442108{col 30}{space 2} .0308899{col 41}{space 1}   11.14{col 50}{space 3}0.000{col 58}{space 4} .2836678{col 71}{space 3} .4047539
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0027471{col 30}{space 2} .0117876{col 41}{space 1}    0.23{col 50}{space 3}0.816{col 58}{space 4}-.0203562{col 71}{space 3} .0258504
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0316346{col 30}{space 2}  .157404{col 41}{space 1}   -0.20{col 50}{space 3}0.841{col 58}{space 4}-.3401408{col 71}{space 3} .2768715
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0029293{col 30}{space 2} .0024632{col 41}{space 1}   -1.19{col 50}{space 3}0.234{col 58}{space 4} -.007757{col 71}{space 3} .0018985
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1112055{col 30}{space 2} .0879281{col 41}{space 1}    1.26{col 50}{space 3}0.206{col 58}{space 4}-.0611304{col 71}{space 3} .2835414
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0684432{col 30}{space 2} .0844881{col 41}{space 1}    0.81{col 50}{space 3}0.418{col 58}{space 4}-.0971504{col 71}{space 3} .2340367
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2178432{col 30}{space 2} .1251683{col 41}{space 1}    1.74{col 50}{space 3}0.082{col 58}{space 4}-.0274822{col 71}{space 3} .4631686
{txt}{space 11}phone {c |}{col 18}{res}{space 2}-.1040755{col 30}{space 2} .0915799{col 41}{space 1}   -1.14{col 50}{space 3}0.256{col 58}{space 4}-.2835688{col 71}{space 3} .0754179
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.2355587{col 30}{space 2} .0927558{col 41}{space 1}   -2.54{col 50}{space 3}0.011{col 58}{space 4}-.4173567{col 71}{space 3}-.0537607
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0153294{col 30}{space 2} .0706239{col 41}{space 1}    0.22{col 50}{space 3}0.828{col 58}{space 4} -.123091{col 71}{space 3} .1537498
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1542687{col 30}{space 2} .0780095{col 41}{space 1}    1.98{col 50}{space 3}0.048{col 58}{space 4} .0013729{col 71}{space 3} .3071645
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1131275{col 30}{space 2} .0778006{col 41}{space 1}   -1.45{col 50}{space 3}0.146{col 58}{space 4}-.2656138{col 71}{space 3} .0393589
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0188478{col 30}{space 2} .0126729{col 41}{space 1}    1.49{col 50}{space 3}0.137{col 58}{space 4}-.0059906{col 71}{space 3} .0436863
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1768164{col 30}{space 2} .0780235{col 41}{space 1}    2.27{col 50}{space 3}0.023{col 58}{space 4} .0238931{col 71}{space 3} .3297396
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.1851185{col 30}{space 2} .2365562{col 41}{space 1}   -0.78{col 50}{space 3}0.434{col 58}{space 4}-.6487601{col 71}{space 3} .2785231
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} -.021633{col 30}{space 2} .1953569{col 41}{space 1}   -0.11{col 50}{space 3}0.912{col 58}{space 4}-.4045255{col 71}{space 3} .3612595
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .482891{col 30}{space 2} .1827195{col 41}{space 1}    2.64{col 50}{space 3}0.008{col 58}{space 4} .1247673{col 71}{space 3} .8410147
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1362663{col 30}{space 2} .1443642{col 41}{space 1}   -0.94{col 50}{space 3}0.345{col 58}{space 4}-.4192149{col 71}{space 3} .1466823
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.5348983{col 30}{space 2} .1560118{col 41}{space 1}   -3.43{col 50}{space 3}0.001{col 58}{space 4}-.8406759{col 71}{space 3}-.2291207
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2785844{col 30}{space 2} .0384077{col 41}{space 1}    7.25{col 50}{space 3}0.000{col 58}{space 4} .2033067{col 71}{space 3}  .353862
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .1504182{col 30}{space 2} .0843198{col 41}{space 1}    1.78{col 50}{space 3}0.074{col 58}{space 4}-.0148456{col 71}{space 3} .3156821
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .2541208{col 30}{space 2} .0676786{col 41}{space 1}    3.75{col 50}{space 3}0.000{col 58}{space 4} .1214731{col 71}{space 3} .3867685
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .2182264{col 30}{space 2} .0706494{col 41}{space 1}    3.09{col 50}{space 3}0.002{col 58}{space 4} .0797562{col 71}{space 3} .3566967
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .1651085{col 30}{space 2} .2323978{col 41}{space 1}    0.71{col 50}{space 3}0.477{col 58}{space 4}-.2903829{col 71}{space 3} .6205999
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .51065417
         {txt}sigma_e {c |} {res}  1.042437
             {txt}rho {c |} {res} .19352786{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,801
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,115

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0711                                         {txt}min = {res}         6
{txt}     between = {res}0.7147                                         {txt}avg = {res}       7.0
{txt}     overall = {res}0.4316                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}25{txt})     =  {res}  4553.52
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,115} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2148664{col 30}{space 2} .0154854{col 41}{space 1}   13.88{col 50}{space 3}0.000{col 58}{space 4} .1845156{col 71}{space 3} .2452172
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0203158{col 30}{space 2} .0074258{col 41}{space 1}    2.74{col 50}{space 3}0.006{col 58}{space 4} .0057615{col 71}{space 3} .0348702
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0204458{col 30}{space 2} .0755274{col 41}{space 1}   -0.27{col 50}{space 3}0.787{col 58}{space 4}-.1684768{col 71}{space 3} .1275852
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}  .002217{col 30}{space 2} .0014262{col 41}{space 1}    1.55{col 50}{space 3}0.120{col 58}{space 4}-.0005783{col 71}{space 3} .0050123
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0568793{col 30}{space 2} .0460965{col 41}{space 1}   -1.23{col 50}{space 3}0.217{col 58}{space 4}-.1472268{col 71}{space 3} .0334682
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1583722{col 30}{space 2} .0443405{col 41}{space 1}    3.57{col 50}{space 3}0.000{col 58}{space 4} .0714663{col 71}{space 3}  .245278
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0238874{col 30}{space 2}  .068192{col 41}{space 1}    0.35{col 50}{space 3}0.726{col 58}{space 4}-.1097665{col 71}{space 3} .1575413
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1004258{col 30}{space 2} .0449456{col 41}{space 1}    2.23{col 50}{space 3}0.025{col 58}{space 4} .0123341{col 71}{space 3} .1885175
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1086303{col 30}{space 2} .0457529{col 41}{space 1}    2.37{col 50}{space 3}0.018{col 58}{space 4} .0189562{col 71}{space 3} .1983044
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.1901435{col 30}{space 2} .0369663{col 41}{space 1}   -5.14{col 50}{space 3}0.000{col 58}{space 4}-.2625962{col 71}{space 3}-.1176908
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} -.038118{col 30}{space 2} .0419604{col 41}{space 1}   -0.91{col 50}{space 3}0.364{col 58}{space 4}-.1203588{col 71}{space 3} .0441229
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0435418{col 30}{space 2}  .034679{col 41}{space 1}   -1.26{col 50}{space 3}0.209{col 58}{space 4}-.1115114{col 71}{space 3} .0244279
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}  .000781{col 30}{space 2} .0017643{col 41}{space 1}    0.44{col 50}{space 3}0.658{col 58}{space 4}-.0026769{col 71}{space 3}  .004239
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1931679{col 30}{space 2} .0378263{col 41}{space 1}    5.11{col 50}{space 3}0.000{col 58}{space 4} .1190297{col 71}{space 3} .2673061
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0473503{col 30}{space 2} .1258629{col 41}{space 1}    0.38{col 50}{space 3}0.707{col 58}{space 4}-.1993364{col 71}{space 3} .2940369
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1087883{col 30}{space 2} .0917858{col 41}{space 1}    1.19{col 50}{space 3}0.236{col 58}{space 4}-.0711086{col 71}{space 3} .2886851
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.0844177{col 30}{space 2} .1023209{col 41}{space 1}   -0.83{col 50}{space 3}0.409{col 58}{space 4} -.284963{col 71}{space 3} .1161275
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1890375{col 30}{space 2} .0808139{col 41}{space 1}   -2.34{col 50}{space 3}0.019{col 58}{space 4}-.3474298{col 71}{space 3}-.0306452
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.3213821{col 30}{space 2} .0772184{col 41}{space 1}   -4.16{col 50}{space 3}0.000{col 58}{space 4}-.4727275{col 71}{space 3}-.1700368
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .5339018{col 30}{space 2} .0234373{col 41}{space 1}   22.78{col 50}{space 3}0.000{col 58}{space 4} .4879655{col 71}{space 3}  .579838
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.0594448{col 30}{space 2} .0446643{col 41}{space 1}   -1.33{col 50}{space 3}0.183{col 58}{space 4}-.1469853{col 71}{space 3} .0280956
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .0677661{col 30}{space 2} .0435806{col 41}{space 1}    1.55{col 50}{space 3}0.120{col 58}{space 4}-.0176502{col 71}{space 3} .1531824
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3774132{col 30}{space 2} .0421261{col 41}{space 1}    8.96{col 50}{space 3}0.000{col 58}{space 4} .2948476{col 71}{space 3} .4599787
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .2072948{col 30}{space 2} .0415851{col 41}{space 1}    4.98{col 50}{space 3}0.000{col 58}{space 4} .1257894{col 71}{space 3} .2888001
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .3551207{col 30}{space 2} .0439632{col 41}{space 1}    8.08{col 50}{space 3}0.000{col 58}{space 4} .2689544{col 71}{space 3}  .441287
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.1048321{col 30}{space 2} .1327627{col 41}{space 1}   -0.79{col 50}{space 3}0.430{col 58}{space 4}-.3650422{col 71}{space 3} .1553779
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .51491937
         {txt}sigma_e {c |} {res} 1.1866875
             {txt}rho {c |} {res} .15844797{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S13_balance.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean _cons)
{res}{txt}(note: file S13_balance.rtf not found)
(output written to {browse  `"S13_balance.rtf"'})

{com}. 
. 
. 
. eststo clear
{txt}
{com}. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    33,152
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    10,109

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0370                                         {txt}min = {res}         1
{txt}     between = {res}0.6233                                         {txt}avg = {res}       3.3
{txt}     overall = {res}0.4575                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 20598.61
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:10,109} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}  .001369{col 30}{space 2} .0087206{col 41}{space 1}    0.16{col 50}{space 3}0.875{col 58}{space 4}-.0157229{col 71}{space 3}  .018461
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0034918{col 30}{space 2} .0043747{col 41}{space 1}    0.80{col 50}{space 3}0.425{col 58}{space 4}-.0050825{col 71}{space 3} .0120661
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1140719{col 30}{space 2} .0455505{col 41}{space 1}   -2.50{col 50}{space 3}0.012{col 58}{space 4}-.2033493{col 71}{space 3}-.0247946
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0049788{col 30}{space 2} .0008355{col 41}{space 1}   -5.96{col 50}{space 3}0.000{col 58}{space 4}-.0066163{col 71}{space 3}-.0033413
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  -.02131{col 30}{space 2}  .028881{col 41}{space 1}   -0.74{col 50}{space 3}0.461{col 58}{space 4}-.0779157{col 71}{space 3} .0352958
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2072943{col 30}{space 2} .0234535{col 41}{space 1}    8.84{col 50}{space 3}0.000{col 58}{space 4} .1613264{col 71}{space 3} .2532623
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1509656{col 30}{space 2} .0430774{col 41}{space 1}    3.50{col 50}{space 3}0.000{col 58}{space 4} .0665355{col 71}{space 3} .2353957
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2135443{col 30}{space 2} .0280185{col 41}{space 1}    7.62{col 50}{space 3}0.000{col 58}{space 4} .1586291{col 71}{space 3} .2684595
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2875132{col 30}{space 2} .0334057{col 41}{space 1}    8.61{col 50}{space 3}0.000{col 58}{space 4} .2220392{col 71}{space 3} .3529872
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2226665{col 30}{space 2} .0294519{col 41}{space 1}    7.56{col 50}{space 3}0.000{col 58}{space 4} .1649419{col 71}{space 3} .2803911
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2386878{col 30}{space 2} .0266347{col 41}{space 1}    8.96{col 50}{space 3}0.000{col 58}{space 4} .1864848{col 71}{space 3} .2908908
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0482429{col 30}{space 2} .0215465{col 41}{space 1}   -2.24{col 50}{space 3}0.025{col 58}{space 4}-.0904732{col 71}{space 3}-.0060125
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0002941{col 30}{space 2} .0014456{col 41}{space 1}    0.20{col 50}{space 3}0.839{col 58}{space 4}-.0025393{col 71}{space 3} .0031275
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0164579{col 30}{space 2} .0261935{col 41}{space 1}    0.63{col 50}{space 3}0.530{col 58}{space 4}-.0348805{col 71}{space 3} .0677963
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.1352205{col 30}{space 2} .0681789{col 41}{space 1}   -1.98{col 50}{space 3}0.047{col 58}{space 4}-.2688487{col 71}{space 3}-.0015923
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6502892{col 30}{space 2} .0468387{col 41}{space 1}   13.88{col 50}{space 3}0.000{col 58}{space 4}  .558487{col 71}{space 3} .7420914
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8779506{col 30}{space 2}  .053226{col 41}{space 1}   16.49{col 50}{space 3}0.000{col 58}{space 4} .7736296{col 71}{space 3} .9822717
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .5819708{col 30}{space 2} .0544389{col 41}{space 1}   10.69{col 50}{space 3}0.000{col 58}{space 4} .4752725{col 71}{space 3} .6886691
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .5541723{col 30}{space 2} .0429726{col 41}{space 1}   12.90{col 50}{space 3}0.000{col 58}{space 4} .4699476{col 71}{space 3}  .638397
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1615647{col 30}{space 2} .0131219{col 41}{space 1}  -12.31{col 50}{space 3}0.000{col 58}{space 4}-.1872832{col 71}{space 3}-.1358463
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.7088905{col 30}{space 2}   .05352{col 41}{space 1}  -13.25{col 50}{space 3}0.000{col 58}{space 4}-.8137878{col 71}{space 3}-.6039931
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-2.026985{col 30}{space 2} .0467771{col 41}{space 1}  -43.33{col 50}{space 3}0.000{col 58}{space 4}-2.118666{col 71}{space 3}-1.935304
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-1.522223{col 30}{space 2} .0534363{col 41}{space 1}  -28.49{col 50}{space 3}0.000{col 58}{space 4}-1.626956{col 71}{space 3}-1.417489
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-1.085988{col 30}{space 2}   .08213{col 41}{space 1}  -13.22{col 50}{space 3}0.000{col 58}{space 4} -1.24696{col 71}{space 3}-.9250161
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2}-.2537361{col 30}{space 2} .0555824{col 41}{space 1}   -4.57{col 50}{space 3}0.000{col 58}{space 4}-.3626756{col 71}{space 3}-.1447967
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2} -.276215{col 30}{space 2} .1031188{col 41}{space 1}   -2.68{col 50}{space 3}0.007{col 58}{space 4}-.4783242{col 71}{space 3}-.0741058
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.1034427{col 30}{space 2}  .093939{col 41}{space 1}   -1.10{col 50}{space 3}0.271{col 58}{space 4}-.2875596{col 71}{space 3} .0806743
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}-.0525924{col 30}{space 2} .0958916{col 41}{space 1}   -0.55{col 50}{space 3}0.583{col 58}{space 4}-.2405364{col 71}{space 3} .1353516
{txt}{space 11}2012  {c |}{col 18}{res}{space 2}-.0590489{col 30}{space 2} .0947367{col 41}{space 1}   -0.62{col 50}{space 3}0.533{col 58}{space 4}-.2447295{col 71}{space 3} .1266316
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0946832{col 30}{space 2} .0960568{col 41}{space 1}    0.99{col 50}{space 3}0.324{col 58}{space 4}-.0935847{col 71}{space 3} .2829512
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0134956{col 30}{space 2} .0991843{col 41}{space 1}   -0.14{col 50}{space 3}0.892{col 58}{space 4}-.2078932{col 71}{space 3}  .180902
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .2687826{col 30}{space 2} .0960202{col 41}{space 1}    2.80{col 50}{space 3}0.005{col 58}{space 4} .0805864{col 71}{space 3} .4569787
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}  .122154{col 30}{space 2} .1043073{col 41}{space 1}    1.17{col 50}{space 3}0.242{col 58}{space 4}-.0822846{col 71}{space 3} .3265926
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .2928854{col 30}{space 2} .0992108{col 41}{space 1}    2.95{col 50}{space 3}0.003{col 58}{space 4} .0984359{col 71}{space 3} .4873349
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .2400637{col 30}{space 2} .0981512{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4} .0476908{col 71}{space 3} .4324366
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.358334{col 30}{space 2} .1167744{col 41}{space 1}   37.32{col 50}{space 3}0.000{col 58}{space 4} 4.129461{col 71}{space 3} 4.587208
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .84536461
         {txt}sigma_e {c |} {res} 1.3768427
             {txt}rho {c |} {res} .27377358{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,449
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,096

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0322                                         {txt}min = {res}         1
{txt}     between = {res}0.3552                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2825                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}21{txt})     =  {res}  1789.19
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,096} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0287863{col 30}{space 2} .0134297{col 41}{space 1}    2.14{col 50}{space 3}0.032{col 58}{space 4} .0024647{col 71}{space 3}  .055108
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0098675{col 30}{space 2}  .009607{col 41}{space 1}    1.03{col 50}{space 3}0.304{col 58}{space 4}-.0089619{col 71}{space 3} .0286968
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0195566{col 30}{space 2} .0813938{col 41}{space 1}    0.24{col 50}{space 3}0.810{col 58}{space 4}-.1399723{col 71}{space 3} .1790854
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0055142{col 30}{space 2} .0013149{col 41}{space 1}   -4.19{col 50}{space 3}0.000{col 58}{space 4}-.0080914{col 71}{space 3}-.0029371
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0486086{col 30}{space 2}   .04982{col 41}{space 1}    0.98{col 50}{space 3}0.329{col 58}{space 4}-.0490367{col 71}{space 3} .1462539
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2305036{col 30}{space 2} .0400403{col 41}{space 1}    5.76{col 50}{space 3}0.000{col 58}{space 4}  .152026{col 71}{space 3} .3089812
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0270974{col 30}{space 2}  .195694{col 41}{space 1}   -0.14{col 50}{space 3}0.890{col 58}{space 4}-.4106507{col 71}{space 3} .3564559
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .216771{col 30}{space 2} .0473042{col 41}{space 1}    4.58{col 50}{space 3}0.000{col 58}{space 4} .1240566{col 71}{space 3} .3094855
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4054204{col 30}{space 2} .0566973{col 41}{space 1}    7.15{col 50}{space 3}0.000{col 58}{space 4} .2942957{col 71}{space 3} .5165451
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .068975{col 30}{space 2} .0867271{col 41}{space 1}    0.80{col 50}{space 3}0.426{col 58}{space 4}-.1010071{col 71}{space 3}  .238957
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .253406{col 30}{space 2} .0665983{col 41}{space 1}    3.80{col 50}{space 3}0.000{col 58}{space 4} .1228757{col 71}{space 3} .3839363
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0950872{col 30}{space 2} .0368725{col 41}{space 1}   -2.58{col 50}{space 3}0.010{col 58}{space 4} -.167356{col 71}{space 3}-.0228185
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0098932{col 30}{space 2} .0060824{col 41}{space 1}   -1.63{col 50}{space 3}0.104{col 58}{space 4}-.0218145{col 71}{space 3} .0020281
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2477708{col 30}{space 2} .0377733{col 41}{space 1}    6.56{col 50}{space 3}0.000{col 58}{space 4} .1737366{col 71}{space 3} .3218051
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .3507062{col 30}{space 2} .3550367{col 41}{space 1}    0.99{col 50}{space 3}0.323{col 58}{space 4}-.3451529{col 71}{space 3} 1.046565
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4905958{col 30}{space 2} .0736445{col 41}{space 1}    6.66{col 50}{space 3}0.000{col 58}{space 4} .3462552{col 71}{space 3} .6349364
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6086785{col 30}{space 2} .0878983{col 41}{space 1}    6.92{col 50}{space 3}0.000{col 58}{space 4} .4364009{col 71}{space 3} .7809561
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .7764273{col 30}{space 2} .1543642{col 41}{space 1}    5.03{col 50}{space 3}0.000{col 58}{space 4} .4738791{col 71}{space 3} 1.078976
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4742145{col 30}{space 2} .0858811{col 41}{space 1}    5.52{col 50}{space 3}0.000{col 58}{space 4} .3058906{col 71}{space 3} .6425385
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1171815{col 30}{space 2} .0193615{col 41}{space 1}   -6.05{col 50}{space 3}0.000{col 58}{space 4}-.1551294{col 71}{space 3}-.0792336
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.2280541{col 30}{space 2} .0277736{col 41}{space 1}   -8.21{col 50}{space 3}0.000{col 58}{space 4}-.2824893{col 71}{space 3} -.173619
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  2.17013{col 30}{space 2} .1055074{col 41}{space 1}   20.57{col 50}{space 3}0.000{col 58}{space 4} 1.963339{col 71}{space 3} 2.376921
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .84036423
         {txt}sigma_e {c |} {res} 1.0740647
             {txt}rho {c |} {res}  .3797192{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,598
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,401

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0428                                         {txt}min = {res}         3
{txt}     between = {res}0.6501                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.4556                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}22{txt})     =  {res}  3869.98
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,401} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}-.0114948{col 30}{space 2} .0195312{col 41}{space 1}   -0.59{col 50}{space 3}0.556{col 58}{space 4}-.0497752{col 71}{space 3} .0267856
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0099949{col 30}{space 2} .0123405{col 41}{space 1}    0.81{col 50}{space 3}0.418{col 58}{space 4}-.0141921{col 71}{space 3} .0341819
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.3987367{col 30}{space 2} .1051466{col 41}{space 1}   -3.79{col 50}{space 3}0.000{col 58}{space 4}-.6048203{col 71}{space 3}-.1926531
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0078703{col 30}{space 2}   .00211{col 41}{space 1}   -3.73{col 50}{space 3}0.000{col 58}{space 4}-.0120059{col 71}{space 3}-.0037347
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.2046857{col 30}{space 2} .0665178{col 41}{space 1}   -3.08{col 50}{space 3}0.002{col 58}{space 4}-.3350582{col 71}{space 3}-.0743132
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2653992{col 30}{space 2} .0632832{col 41}{space 1}    4.19{col 50}{space 3}0.000{col 58}{space 4} .1413664{col 71}{space 3} .3894319
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0948985{col 30}{space 2} .1593069{col 41}{space 1}    0.60{col 50}{space 3}0.551{col 58}{space 4}-.2173373{col 71}{space 3} .4071343
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3128257{col 30}{space 2} .0711426{col 41}{space 1}    4.40{col 50}{space 3}0.000{col 58}{space 4} .1733889{col 71}{space 3} .4522626
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .5104926{col 30}{space 2} .1160964{col 41}{space 1}    4.40{col 50}{space 3}0.000{col 58}{space 4} .2829477{col 71}{space 3} .7380374
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .280394{col 30}{space 2} .0761215{col 41}{space 1}    3.68{col 50}{space 3}0.000{col 58}{space 4} .1311986{col 71}{space 3} .4295894
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3476724{col 30}{space 2} .0565945{col 41}{space 1}    6.14{col 50}{space 3}0.000{col 58}{space 4} .2367492{col 71}{space 3} .4585955
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0495035{col 30}{space 2} .0477608{col 41}{space 1}   -1.04{col 50}{space 3}0.300{col 58}{space 4} -.143113{col 71}{space 3}  .044106
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0116567{col 30}{space 2} .0353206{col 41}{space 1}   -0.33{col 50}{space 3}0.741{col 58}{space 4}-.0808839{col 71}{space 3} .0575705
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0065409{col 30}{space 2} .0677398{col 41}{space 1}    0.10{col 50}{space 3}0.923{col 58}{space 4}-.1262266{col 71}{space 3} .1393084
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1958722{col 30}{space 2} .3686351{col 41}{space 1}    0.53{col 50}{space 3}0.595{col 58}{space 4}-.5266394{col 71}{space 3} .9183838
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .8297504{col 30}{space 2}  .130032{col 41}{space 1}    6.38{col 50}{space 3}0.000{col 58}{space 4} .5748924{col 71}{space 3} 1.084608
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.035751{col 30}{space 2} .1688129{col 41}{space 1}    6.14{col 50}{space 3}0.000{col 58}{space 4} .7048838{col 71}{space 3} 1.366618
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .6546406{col 30}{space 2} .1244799{col 41}{space 1}    5.26{col 50}{space 3}0.000{col 58}{space 4} .4106645{col 71}{space 3} .8986168
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .8219225{col 30}{space 2} .1209968{col 41}{space 1}    6.79{col 50}{space 3}0.000{col 58}{space 4} .5847731{col 71}{space 3} 1.059072
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2493733{col 30}{space 2} .0342799{col 41}{space 1}   -7.27{col 50}{space 3}0.000{col 58}{space 4}-.3165608{col 71}{space 3}-.1821859
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} -.263318{col 30}{space 2} .0570696{col 41}{space 1}   -4.61{col 50}{space 3}0.000{col 58}{space 4}-.3751724{col 71}{space 3}-.1514636
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.0188165{col 30}{space 2} .0480353{col 41}{space 1}   -0.39{col 50}{space 3}0.695{col 58}{space 4}-.1129639{col 71}{space 3} .0753308
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.398247{col 30}{space 2} .1721707{col 41}{space 1}   25.55{col 50}{space 3}0.000{col 58}{space 4} 4.060799{col 71}{space 3} 4.735696
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .85016002
         {txt}sigma_e {c |} {res} 1.4784537
             {txt}rho {c |} {res} .24849505{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,952
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,977

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0223                                         {txt}min = {res}         1
{txt}     between = {res}0.3492                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.2461                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}21{txt})     =  {res}  1885.13
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,977} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2293628{col 30}{space 2} .0378954{col 41}{space 1}    6.05{col 50}{space 3}0.000{col 58}{space 4} .1550891{col 71}{space 3} .3036365
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0138984{col 30}{space 2} .0077639{col 41}{space 1}    1.79{col 50}{space 3}0.073{col 58}{space 4}-.0013185{col 71}{space 3} .0291154
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.081525{col 30}{space 2} .1199056{col 41}{space 1}   -0.68{col 50}{space 3}0.497{col 58}{space 4}-.3165357{col 71}{space 3} .1534858
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0008506{col 30}{space 2} .0017654{col 41}{space 1}    0.48{col 50}{space 3}0.630{col 58}{space 4}-.0026095{col 71}{space 3} .0043106
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0883544{col 30}{space 2} .0690933{col 41}{space 1}    1.28{col 50}{space 3}0.201{col 58}{space 4} -.047066{col 71}{space 3} .2237747
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3143103{col 30}{space 2}  .052619{col 41}{space 1}    5.97{col 50}{space 3}0.000{col 58}{space 4} .2111788{col 71}{space 3} .4174417
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2363789{col 30}{space 2}  .099757{col 41}{space 1}    2.37{col 50}{space 3}0.018{col 58}{space 4} .0408588{col 71}{space 3} .4318989
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1534596{col 30}{space 2} .0818626{col 41}{space 1}    1.87{col 50}{space 3}0.061{col 58}{space 4}-.0069881{col 71}{space 3} .3139073
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2286508{col 30}{space 2} .1092206{col 41}{space 1}    2.09{col 50}{space 3}0.036{col 58}{space 4} .0145824{col 71}{space 3} .4427192
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2830635{col 30}{space 2} .0890408{col 41}{space 1}    3.18{col 50}{space 3}0.001{col 58}{space 4} .1085467{col 71}{space 3} .4575803
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1726772{col 30}{space 2} .0721625{col 41}{space 1}   -2.39{col 50}{space 3}0.017{col 58}{space 4}-.3141131{col 71}{space 3}-.0312413
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1413324{col 30}{space 2} .0534117{col 41}{space 1}   -2.65{col 50}{space 3}0.008{col 58}{space 4}-.2460175{col 71}{space 3}-.0366473
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} -.001227{col 30}{space 2} .0018778{col 41}{space 1}   -0.65{col 50}{space 3}0.513{col 58}{space 4}-.0049075{col 71}{space 3} .0024535
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0232348{col 30}{space 2} .2615698{col 41}{space 1}    0.09{col 50}{space 3}0.929{col 58}{space 4}-.4894325{col 71}{space 3} .5359021
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1743966{col 30}{space 2} .1333973{col 41}{space 1}    1.31{col 50}{space 3}0.191{col 58}{space 4}-.0870572{col 71}{space 3} .4358504
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5214952{col 30}{space 2} .1081547{col 41}{space 1}    4.82{col 50}{space 3}0.000{col 58}{space 4} .3095158{col 71}{space 3} .7334745
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .744522{col 30}{space 2}   .13606{col 41}{space 1}    5.47{col 50}{space 3}0.000{col 58}{space 4} .4778493{col 71}{space 3} 1.011195
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2927002{col 30}{space 2} .1197813{col 41}{space 1}    2.44{col 50}{space 3}0.015{col 58}{space 4} .0579331{col 71}{space 3} .5274673
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .6603793{col 30}{space 2} .0944877{col 41}{space 1}    6.99{col 50}{space 3}0.000{col 58}{space 4} .4751868{col 71}{space 3} .8455718
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2958678{col 30}{space 2} .0445795{col 41}{space 1}   -6.64{col 50}{space 3}0.000{col 58}{space 4} -.383242{col 71}{space 3}-.2084935
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .0234264{col 30}{space 2} .0423644{col 41}{space 1}    0.55{col 50}{space 3}0.580{col 58}{space 4}-.0596064{col 71}{space 3} .1064591
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.085989{col 30}{space 2} .1346492{col 41}{space 1}   30.35{col 50}{space 3}0.000{col 58}{space 4} 3.822081{col 71}{space 3} 4.349896
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .71672973
         {txt}sigma_e {c |} {res} 1.5029883
             {txt}rho {c |} {res} .18527288{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,770
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,203

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0283                                         {txt}min = {res}         3
{txt}     between = {res}0.5371                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.3483                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1622.90
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,203} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0074214{col 30}{space 2} .0255904{col 41}{space 1}    0.29{col 50}{space 3}0.772{col 58}{space 4}-.0427348{col 71}{space 3} .0575777
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0069225{col 30}{space 2} .0097962{col 41}{space 1}    0.71{col 50}{space 3}0.480{col 58}{space 4}-.0122777{col 71}{space 3} .0261226
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0632079{col 30}{space 2} .1102599{col 41}{space 1}   -0.57{col 50}{space 3}0.566{col 58}{space 4}-.2793134{col 71}{space 3} .1528976
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0040333{col 30}{space 2}  .002115{col 41}{space 1}    1.91{col 50}{space 3}0.057{col 58}{space 4}-.0001121{col 71}{space 3} .0081787
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0703379{col 30}{space 2} .0825692{col 41}{space 1}    0.85{col 50}{space 3}0.394{col 58}{space 4}-.0914948{col 71}{space 3} .2321707
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0978295{col 30}{space 2} .0577515{col 41}{space 1}    1.69{col 50}{space 3}0.090{col 58}{space 4}-.0153614{col 71}{space 3} .2110204
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1387253{col 30}{space 2} .0705341{col 41}{space 1}    1.97{col 50}{space 3}0.049{col 58}{space 4} .0004811{col 71}{space 3} .2769695
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .231848{col 30}{space 2} .0713494{col 41}{space 1}    3.25{col 50}{space 3}0.001{col 58}{space 4} .0920057{col 71}{space 3} .3716903
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2105429{col 30}{space 2} .0896197{col 41}{space 1}    2.35{col 50}{space 3}0.019{col 58}{space 4} .0348916{col 71}{space 3} .3861942
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2378279{col 30}{space 2}   .08974{col 41}{space 1}    2.65{col 50}{space 3}0.008{col 58}{space 4} .0619406{col 71}{space 3} .4137151
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2928914{col 30}{space 2} .0685528{col 41}{space 1}    4.27{col 50}{space 3}0.000{col 58}{space 4} .1585305{col 71}{space 3} .4272524
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0238546{col 30}{space 2} .0994483{col 41}{space 1}   -0.24{col 50}{space 3}0.810{col 58}{space 4}-.2187697{col 71}{space 3} .1710606
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0357919{col 30}{space 2} .0148659{col 41}{space 1}   -2.41{col 50}{space 3}0.016{col 58}{space 4}-.0649284{col 71}{space 3}-.0066553
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1382297{col 30}{space 2} .1219107{col 41}{space 1}    1.13{col 50}{space 3}0.257{col 58}{space 4}-.1007109{col 71}{space 3} .3771702
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} -.328198{col 30}{space 2}  .117385{col 41}{space 1}   -2.80{col 50}{space 3}0.005{col 58}{space 4}-.5582683{col 71}{space 3}-.0981277
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} 1.018629{col 30}{space 2} .1436961{col 41}{space 1}    7.09{col 50}{space 3}0.000{col 58}{space 4} .7369894{col 71}{space 3} 1.300268
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.089747{col 30}{space 2} .1361843{col 41}{space 1}    8.00{col 50}{space 3}0.000{col 58}{space 4} .8228303{col 71}{space 3} 1.356663
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4058463{col 30}{space 2} .1410896{col 41}{space 1}    2.88{col 50}{space 3}0.004{col 58}{space 4} .1293157{col 71}{space 3} .6823769
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1712209{col 30}{space 2} .1140073{col 41}{space 1}    1.50{col 50}{space 3}0.133{col 58}{space 4}-.0522293{col 71}{space 3} .3946711
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1471586{col 30}{space 2} .0420913{col 41}{space 1}   -3.50{col 50}{space 3}0.000{col 58}{space 4}-.2296561{col 71}{space 3}-.0646612
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.2720118{col 30}{space 2} .0641474{col 41}{space 1}   -4.24{col 50}{space 3}0.000{col 58}{space 4}-.3977384{col 71}{space 3}-.1462853
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}  -.29414{col 30}{space 2} .0603696{col 41}{space 1}   -4.87{col 50}{space 3}0.000{col 58}{space 4}-.4124622{col 71}{space 3}-.1758179
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.0553834{col 30}{space 2}  .059212{col 41}{space 1}   -0.94{col 50}{space 3}0.350{col 58}{space 4}-.1714368{col 71}{space 3} .0606699
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.383572{col 30}{space 2} .1849141{col 41}{space 1}   18.30{col 50}{space 3}0.000{col 58}{space 4} 3.021147{col 71}{space 3} 3.745997
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .81684771
         {txt}sigma_e {c |} {res} 1.3861447
             {txt}rho {c |} {res}  .2577573{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     1,582
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}       317

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0278                                         {txt}min = {res}         4
{txt}     between = {res}0.6138                                         {txt}avg = {res}       5.0
{txt}     overall = {res}0.4180                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}23{txt})     =  {res}   610.43
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:317} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0175083{col 30}{space 2} .0393598{col 41}{space 1}    0.44{col 50}{space 3}0.656{col 58}{space 4}-.0596355{col 71}{space 3} .0946522
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0487069{col 30}{space 2}  .023483{col 41}{space 1}   -2.07{col 50}{space 3}0.038{col 58}{space 4}-.0947327{col 71}{space 3} -.002681
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0579495{col 30}{space 2} .2380562{col 41}{space 1}   -0.24{col 50}{space 3}0.808{col 58}{space 4}-.5245311{col 71}{space 3} .4086321
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0108202{col 30}{space 2} .0044471{col 41}{space 1}   -2.43{col 50}{space 3}0.015{col 58}{space 4}-.0195363{col 71}{space 3}-.0021041
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2171356{col 30}{space 2} .1445095{col 41}{space 1}    1.50{col 50}{space 3}0.133{col 58}{space 4}-.0660977{col 71}{space 3}  .500369
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1483816{col 30}{space 2} .1427124{col 41}{space 1}    1.04{col 50}{space 3}0.298{col 58}{space 4}-.1313295{col 71}{space 3} .4280927
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0095351{col 30}{space 2} .1728168{col 41}{space 1}    0.06{col 50}{space 3}0.956{col 58}{space 4}-.3291795{col 71}{space 3} .3482497
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1709178{col 30}{space 2} .1179502{col 41}{space 1}    1.45{col 50}{space 3}0.147{col 58}{space 4}-.0602604{col 71}{space 3} .4020959
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1427547{col 30}{space 2} .1254784{col 41}{space 1}    1.14{col 50}{space 3}0.255{col 58}{space 4}-.1031786{col 71}{space 3} .3886879
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0907414{col 30}{space 2} .0898633{col 41}{space 1}    1.01{col 50}{space 3}0.313{col 58}{space 4}-.0853874{col 71}{space 3} .2668702
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3985859{col 30}{space 2} .1038158{col 41}{space 1}    3.84{col 50}{space 3}0.000{col 58}{space 4} .1951107{col 71}{space 3} .6020612
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0990042{col 30}{space 2}  .106844{col 41}{space 1}   -0.93{col 50}{space 3}0.354{col 58}{space 4}-.3084146{col 71}{space 3} .1104063
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0110013{col 30}{space 2}  .014403{col 41}{space 1}   -0.76{col 50}{space 3}0.445{col 58}{space 4}-.0392307{col 71}{space 3} .0172281
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.1031031{col 30}{space 2} .1004077{col 41}{space 1}   -1.03{col 50}{space 3}0.304{col 58}{space 4}-.2998986{col 71}{space 3} .0936923
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .5592155{col 30}{space 2} .3644243{col 41}{space 1}    1.53{col 50}{space 3}0.125{col 58}{space 4}-.1550429{col 71}{space 3} 1.273474
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  1.58992{col 30}{space 2} .2758973{col 41}{space 1}    5.76{col 50}{space 3}0.000{col 58}{space 4} 1.049172{col 71}{space 3} 2.130669
{txt}electricity_mean {c |}{col 18}{res}{space 2}  1.21435{col 30}{space 2} .2805001{col 41}{space 1}    4.33{col 50}{space 3}0.000{col 58}{space 4} .6645799{col 71}{space 3}  1.76412
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0860945{col 30}{space 2} .2234266{col 41}{space 1}   -0.39{col 50}{space 3}0.700{col 58}{space 4}-.5240027{col 71}{space 3} .3518136
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1282424{col 30}{space 2} .2386663{col 41}{space 1}    0.54{col 50}{space 3}0.591{col 58}{space 4}-.3395351{col 71}{space 3} .5960198
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.3183147{col 30}{space 2} .0619403{col 41}{space 1}   -5.14{col 50}{space 3}0.000{col 58}{space 4}-.4397154{col 71}{space 3} -.196914
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.1299122{col 30}{space 2} .1123203{col 41}{space 1}   -1.16{col 50}{space 3}0.247{col 58}{space 4} -.350056{col 71}{space 3} .0902317
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.1942862{col 30}{space 2} .0885456{col 41}{space 1}   -2.19{col 50}{space 3}0.028{col 58}{space 4}-.3678325{col 71}{space 3}  -.02074
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .1476069{col 30}{space 2} .0970944{col 41}{space 1}    1.52{col 50}{space 3}0.128{col 58}{space 4}-.0426946{col 71}{space 3} .3379084
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.205455{col 30}{space 2} .3942361{col 41}{space 1}   10.67{col 50}{space 3}0.000{col 58}{space 4} 3.432767{col 71}{space 3} 4.978144
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .90733732
         {txt}sigma_e {c |} {res} 1.3718588
             {txt}rho {c |} {res}  .3043189{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,801
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,115

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0607                                         {txt}min = {res}         6
{txt}     between = {res}0.4727                                         {txt}avg = {res}       7.0
{txt}     overall = {res}0.2840                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}25{txt})     =  {res}  1627.04
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,115} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}-.0190969{col 30}{space 2}  .017542{col 41}{space 1}   -1.09{col 50}{space 3}0.276{col 58}{space 4}-.0534786{col 71}{space 3} .0152849
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0059344{col 30}{space 2} .0101007{col 41}{space 1}   -0.59{col 50}{space 3}0.557{col 58}{space 4}-.0257314{col 71}{space 3} .0138625
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.013773{col 30}{space 2} .1005809{col 41}{space 1}   -0.14{col 50}{space 3}0.891{col 58}{space 4} -.210908{col 71}{space 3} .1833619
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.003159{col 30}{space 2} .0023454{col 41}{space 1}   -1.35{col 50}{space 3}0.178{col 58}{space 4} -.007756{col 71}{space 3} .0014379
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0789254{col 30}{space 2} .0642194{col 41}{space 1}    1.23{col 50}{space 3}0.219{col 58}{space 4}-.0469423{col 71}{space 3} .2047932
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1971704{col 30}{space 2} .0552948{col 41}{space 1}    3.57{col 50}{space 3}0.000{col 58}{space 4} .0887946{col 71}{space 3} .3055462
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2077623{col 30}{space 2} .0819832{col 41}{space 1}    2.53{col 50}{space 3}0.011{col 58}{space 4} .0470781{col 71}{space 3} .3684465
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3496788{col 30}{space 2} .0534921{col 41}{space 1}    6.54{col 50}{space 3}0.000{col 58}{space 4} .2448362{col 71}{space 3} .4545215
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4784695{col 30}{space 2} .0547591{col 41}{space 1}    8.74{col 50}{space 3}0.000{col 58}{space 4} .3711435{col 71}{space 3} .5857954
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2039297{col 30}{space 2}  .044774{col 41}{space 1}    4.55{col 50}{space 3}0.000{col 58}{space 4} .1161743{col 71}{space 3} .2916851
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2575187{col 30}{space 2} .0488373{col 41}{space 1}    5.27{col 50}{space 3}0.000{col 58}{space 4} .1617994{col 71}{space 3} .3532381
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0743037{col 30}{space 2} .0402842{col 41}{space 1}    1.84{col 50}{space 3}0.065{col 58}{space 4}-.0046519{col 71}{space 3} .1532593
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0009624{col 30}{space 2} .0023363{col 41}{space 1}    0.41{col 50}{space 3}0.680{col 58}{space 4}-.0036166{col 71}{space 3} .0055415
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.1809893{col 30}{space 2} .0495148{col 41}{space 1}   -3.66{col 50}{space 3}0.000{col 58}{space 4}-.2780365{col 71}{space 3}-.0839422
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1818124{col 30}{space 2} .1770389{col 41}{space 1}    1.03{col 50}{space 3}0.304{col 58}{space 4}-.1651775{col 71}{space 3} .5288024
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .357497{col 30}{space 2} .1314472{col 41}{space 1}    2.72{col 50}{space 3}0.007{col 58}{space 4} .0998652{col 71}{space 3} .6151288
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6012285{col 30}{space 2} .1593126{col 41}{space 1}    3.77{col 50}{space 3}0.000{col 58}{space 4} .2889816{col 71}{space 3} .9134753
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .5386509{col 30}{space 2} .1272202{col 41}{space 1}    4.23{col 50}{space 3}0.000{col 58}{space 4} .2893039{col 71}{space 3} .7879979
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .7380032{col 30}{space 2} .1120139{col 41}{space 1}    6.59{col 50}{space 3}0.000{col 58}{space 4} .5184601{col 71}{space 3} .9575464
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.3091976{col 30}{space 2} .0318632{col 41}{space 1}   -9.70{col 50}{space 3}0.000{col 58}{space 4}-.3716483{col 71}{space 3}-.2467468
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} -.193772{col 30}{space 2} .0521654{col 41}{space 1}   -3.71{col 50}{space 3}0.000{col 58}{space 4}-.2960142{col 71}{space 3}-.0915297
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.1597366{col 30}{space 2} .0524411{col 41}{space 1}   -3.05{col 50}{space 3}0.002{col 58}{space 4}-.2625192{col 71}{space 3}-.0569539
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}  .289892{col 30}{space 2} .0527159{col 41}{space 1}    5.50{col 50}{space 3}0.000{col 58}{space 4} .1865708{col 71}{space 3} .3932133
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1128053{col 30}{space 2} .0535317{col 41}{space 1}    2.11{col 50}{space 3}0.035{col 58}{space 4} .0078851{col 71}{space 3} .2177255
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2155316{col 30}{space 2}  .052755{col 41}{space 1}    4.09{col 50}{space 3}0.000{col 58}{space 4} .1121337{col 71}{space 3} .3189296
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.361555{col 30}{space 2} .2061957{col 41}{space 1}   16.30{col 50}{space 3}0.000{col 58}{space 4} 2.957418{col 71}{space 3} 3.765691
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .90101979
         {txt}sigma_e {c |} {res} 1.4141713
             {txt}rho {c |} {res}  .2887334{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. 
. esttab using  S14_balance.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean _cons)
{res}{txt}(note: file S14_balance.rtf not found)
(output written to {browse  `"S14_balance.rtf"'})

{com}. restore
{txt}
{com}. 
. 
. ********************************************************************************
. *                                 S15-S18                                      *
. ********************************************************************************
. preserve
{txt}
{com}. drop if sum_vill<=1|sum_vill==.
{txt}(4,340 observations deleted)

{com}. 
. drop pdd9_mean no_species_mean hhsize_mean dependent_share_mean head_age_mean female_head_mean head_read_mean motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean weather_shock_mean plot_area_mean other_crop_mean
{txt}
{com}. egen pdd9_mean=mean(pdd9), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_vill=mean(pdd9_vill), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_town=mean(pdd9_town), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_dist=mean(pdd9_dist), by(HHID_panel)
{txt}
{com}. 
. foreach x of varlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. 
. 
. *                                  hh_level                                    *
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9   $xlist  pdd9_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    30,867
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     9,851

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0368                                         {txt}min = {res}         1
{txt}     between = {res}0.4820                                         {txt}avg = {res}       3.1
{txt}     overall = {res}0.3294                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 11252.42
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:9,851} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0819586{col 30}{space 2} .0077653{col 41}{space 1}   10.55{col 50}{space 3}0.000{col 58}{space 4} .0667389{col 71}{space 3} .0971784
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0013545{col 30}{space 2} .0037636{col 41}{space 1}    0.36{col 50}{space 3}0.719{col 58}{space 4} -.006022{col 71}{space 3}  .008731
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.026324{col 30}{space 2} .0407323{col 41}{space 1}   -0.65{col 50}{space 3}0.518{col 58}{space 4}-.1061579{col 71}{space 3}   .05351
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0006922{col 30}{space 2} .0007042{col 41}{space 1}   -0.98{col 50}{space 3}0.326{col 58}{space 4}-.0020724{col 71}{space 3} .0006881
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0074259{col 30}{space 2} .0251842{col 41}{space 1}    0.29{col 50}{space 3}0.768{col 58}{space 4}-.0419343{col 71}{space 3} .0567861
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2655348{col 30}{space 2}  .020883{col 41}{space 1}   12.72{col 50}{space 3}0.000{col 58}{space 4} .2246049{col 71}{space 3} .3064647
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1346904{col 30}{space 2} .0430684{col 41}{space 1}    3.13{col 50}{space 3}0.002{col 58}{space 4} .0502779{col 71}{space 3}  .219103
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1576219{col 30}{space 2} .0254185{col 41}{space 1}    6.20{col 50}{space 3}0.000{col 58}{space 4} .1078025{col 71}{space 3} .2074413
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1463426{col 30}{space 2} .0310146{col 41}{space 1}    4.72{col 50}{space 3}0.000{col 58}{space 4} .0855551{col 71}{space 3} .2071302
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1151191{col 30}{space 2} .0287774{col 41}{space 1}    4.00{col 50}{space 3}0.000{col 58}{space 4} .0587164{col 71}{space 3} .1715218
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .158687{col 30}{space 2} .0245871{col 41}{space 1}    6.45{col 50}{space 3}0.000{col 58}{space 4}  .110497{col 71}{space 3} .2068769
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.104468{col 30}{space 2} .0191022{col 41}{space 1}   -5.47{col 50}{space 3}0.000{col 58}{space 4}-.1419076{col 71}{space 3}-.0670285
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0002823{col 30}{space 2} .0013519{col 41}{space 1}   -0.21{col 50}{space 3}0.835{col 58}{space 4}-.0029321{col 71}{space 3} .0023674
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1161268{col 30}{space 2} .0223937{col 41}{space 1}    5.19{col 50}{space 3}0.000{col 58}{space 4} .0722359{col 71}{space 3} .1600176
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .064843{col 30}{space 2} .0645274{col 41}{space 1}    1.00{col 50}{space 3}0.315{col 58}{space 4}-.0616284{col 71}{space 3} .1913143
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5378286{col 30}{space 2} .0406715{col 41}{space 1}   13.22{col 50}{space 3}0.000{col 58}{space 4}  .458114{col 71}{space 3} .6175432
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7101541{col 30}{space 2} .0479973{col 41}{space 1}   14.80{col 50}{space 3}0.000{col 58}{space 4} .6160812{col 71}{space 3} .8042271
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3771042{col 30}{space 2} .0494178{col 41}{space 1}    7.63{col 50}{space 3}0.000{col 58}{space 4} .2802471{col 71}{space 3} .4739613
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2255629{col 30}{space 2} .0378385{col 41}{space 1}    5.96{col 50}{space 3}0.000{col 58}{space 4} .1514008{col 71}{space 3}  .299725
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0238992{col 30}{space 2} .0115899{col 41}{space 1}    2.06{col 50}{space 3}0.039{col 58}{space 4} .0011835{col 71}{space 3} .0466149
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.4681134{col 30}{space 2} .0506565{col 41}{space 1}   -9.24{col 50}{space 3}0.000{col 58}{space 4}-.5673983{col 71}{space 3}-.3688284
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.525864{col 30}{space 2} .0411508{col 41}{space 1}  -37.08{col 50}{space 3}0.000{col 58}{space 4}-1.606518{col 71}{space 3} -1.44521
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2} -.545996{col 30}{space 2}  .046122{col 41}{space 1}  -11.84{col 50}{space 3}0.000{col 58}{space 4}-.6363936{col 71}{space 3}-.4555985
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.3455537{col 30}{space 2} .0707606{col 41}{space 1}   -4.88{col 50}{space 3}0.000{col 58}{space 4}-.4842419{col 71}{space 3}-.2068656
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .3959624{col 30}{space 2}  .049963{col 41}{space 1}    7.93{col 50}{space 3}0.000{col 58}{space 4} .2980367{col 71}{space 3} .4938881
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.1985194{col 30}{space 2} .0997545{col 41}{space 1}   -1.99{col 50}{space 3}0.047{col 58}{space 4}-.3940346{col 71}{space 3}-.0030042
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0260047{col 30}{space 2}  .090908{col 41}{space 1}    0.29{col 50}{space 3}0.775{col 58}{space 4}-.1521717{col 71}{space 3} .2041811
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0737804{col 30}{space 2}   .09167{col 41}{space 1}    0.80{col 50}{space 3}0.421{col 58}{space 4}-.1058895{col 71}{space 3} .2534503
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0707741{col 30}{space 2} .0939414{col 41}{space 1}    0.75{col 50}{space 3}0.451{col 58}{space 4}-.1133477{col 71}{space 3} .2548959
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0721815{col 30}{space 2} .0919968{col 41}{space 1}    0.78{col 50}{space 3}0.433{col 58}{space 4} -.108129{col 71}{space 3}  .252492
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.1384549{col 30}{space 2} .0944844{col 41}{space 1}   -1.47{col 50}{space 3}0.143{col 58}{space 4} -.323641{col 71}{space 3} .0467312
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .2358489{col 30}{space 2}  .092346{col 41}{space 1}    2.55{col 50}{space 3}0.011{col 58}{space 4}  .054854{col 71}{space 3} .4168437
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.1622173{col 30}{space 2}  .102414{col 41}{space 1}   -1.58{col 50}{space 3}0.113{col 58}{space 4} -.362945{col 71}{space 3} .0385104
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .5349418{col 30}{space 2} .0951487{col 41}{space 1}    5.62{col 50}{space 3}0.000{col 58}{space 4} .3484538{col 71}{space 3} .7214297
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .1344201{col 30}{space 2} .0935271{col 41}{space 1}    1.44{col 50}{space 3}0.151{col 58}{space 4}-.0488896{col 71}{space 3} .3177298
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.474151{col 30}{space 2} .1074823{col 41}{space 1}   41.63{col 50}{space 3}0.000{col 58}{space 4}  4.26349{col 71}{space 3} 4.684813
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .71299548
         {txt}sigma_e {c |} {res} 1.2174577
             {txt}rho {c |} {res} .25538597{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,299
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,149

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0241                                         {txt}min = {res}         1
{txt}     between = {res}0.3041                                         {txt}avg = {res}       3.0
{txt}     overall = {res}0.1931                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}21{txt})     =  {res}  1574.37
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,149} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0559257{col 30}{space 2} .0113883{col 41}{space 1}    4.91{col 50}{space 3}0.000{col 58}{space 4}  .033605{col 71}{space 3} .0782465
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0295173{col 30}{space 2} .0078959{col 41}{space 1}    3.74{col 50}{space 3}0.000{col 58}{space 4} .0140416{col 71}{space 3} .0449929
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.017806{col 30}{space 2} .0649873{col 41}{space 1}   -0.27{col 50}{space 3}0.784{col 58}{space 4}-.1451787{col 71}{space 3} .1095667
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0031933{col 30}{space 2} .0011108{col 41}{space 1}   -2.87{col 50}{space 3}0.004{col 58}{space 4}-.0053704{col 71}{space 3}-.0010162
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0318028{col 30}{space 2} .0413347{col 41}{space 1}    0.77{col 50}{space 3}0.442{col 58}{space 4}-.0492118{col 71}{space 3} .1128173
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3129382{col 30}{space 2} .0335138{col 41}{space 1}    9.34{col 50}{space 3}0.000{col 58}{space 4} .2472524{col 71}{space 3} .3786239
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2653955{col 30}{space 2} .1608956{col 41}{space 1}   -1.65{col 50}{space 3}0.099{col 58}{space 4} -.580745{col 71}{space 3}  .049954
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1943099{col 30}{space 2} .0389161{col 41}{space 1}    4.99{col 50}{space 3}0.000{col 58}{space 4} .1180357{col 71}{space 3} .2705841
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1210324{col 30}{space 2} .0483322{col 41}{space 1}    2.50{col 50}{space 3}0.012{col 58}{space 4} .0263031{col 71}{space 3} .2157617
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0847279{col 30}{space 2} .0725303{col 41}{space 1}    1.17{col 50}{space 3}0.243{col 58}{space 4}-.0574289{col 71}{space 3} .2268847
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1970463{col 30}{space 2} .0523024{col 41}{space 1}    3.77{col 50}{space 3}0.000{col 58}{space 4} .0945356{col 71}{space 3} .2995571
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1495909{col 30}{space 2} .0312261{col 41}{space 1}   -4.79{col 50}{space 3}0.000{col 58}{space 4}-.2107929{col 71}{space 3}-.0883888
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0088492{col 30}{space 2} .0037628{col 41}{space 1}    2.35{col 50}{space 3}0.019{col 58}{space 4} .0014742{col 71}{space 3} .0162242
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2094603{col 30}{space 2} .0321718{col 41}{space 1}    6.51{col 50}{space 3}0.000{col 58}{space 4} .1464047{col 71}{space 3} .2725159
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} 1.210611{col 30}{space 2}  .304925{col 41}{space 1}    3.97{col 50}{space 3}0.000{col 58}{space 4} .6129687{col 71}{space 3} 1.808253
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3864643{col 30}{space 2} .0622347{col 41}{space 1}    6.21{col 50}{space 3}0.000{col 58}{space 4} .2644866{col 71}{space 3} .5084421
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4122138{col 30}{space 2} .0761749{col 41}{space 1}    5.41{col 50}{space 3}0.000{col 58}{space 4} .2629138{col 71}{space 3} .5615138
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .519036{col 30}{space 2} .1368223{col 41}{space 1}    3.79{col 50}{space 3}0.000{col 58}{space 4} .2508692{col 71}{space 3} .7872029
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1457539{col 30}{space 2} .0693541{col 41}{space 1}    2.10{col 50}{space 3}0.036{col 58}{space 4} .0098223{col 71}{space 3} .2816855
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}  .084172{col 30}{space 2} .0164272{col 41}{space 1}    5.12{col 50}{space 3}0.000{col 58}{space 4} .0519753{col 71}{space 3} .1163686
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.2055863{col 30}{space 2}  .023789{col 41}{space 1}   -8.64{col 50}{space 3}0.000{col 58}{space 4}-.2522119{col 71}{space 3}-.1589607
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.020042{col 30}{space 2} .0851649{col 41}{space 1}   35.46{col 50}{space 3}0.000{col 58}{space 4} 2.853122{col 71}{space 3} 3.186962
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .66624619
         {txt}sigma_e {c |} {res} 1.0637368
             {txt}rho {c |} {res} .28175598{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,301
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,381

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0311                                         {txt}min = {res}         1
{txt}     between = {res}0.4111                                         {txt}avg = {res}       3.1
{txt}     overall = {res}0.2793                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1407.84
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,381} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1205717{col 30}{space 2} .0196095{col 41}{space 1}    6.15{col 50}{space 3}0.000{col 58}{space 4} .0821378{col 71}{space 3} .1590055
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0053696{col 30}{space 2} .0116691{col 41}{space 1}   -0.46{col 50}{space 3}0.645{col 58}{space 4}-.0282405{col 71}{space 3} .0175014
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2882169{col 30}{space 2} .1071276{col 41}{space 1}   -2.69{col 50}{space 3}0.007{col 58}{space 4}-.4981832{col 71}{space 3}-.0782506
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0020594{col 30}{space 2}   .00182{col 41}{space 1}   -1.13{col 50}{space 3}0.258{col 58}{space 4}-.0056266{col 71}{space 3} .0015078
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} -.114962{col 30}{space 2} .0624425{col 41}{space 1}   -1.84{col 50}{space 3}0.066{col 58}{space 4}-.2373471{col 71}{space 3} .0074231
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2912422{col 30}{space 2} .0599486{col 41}{space 1}    4.86{col 50}{space 3}0.000{col 58}{space 4} .1737451{col 71}{space 3} .4087393
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2337465{col 30}{space 2} .1971983{col 41}{space 1}    1.19{col 50}{space 3}0.236{col 58}{space 4} -.152755{col 71}{space 3}  .620248
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0727084{col 30}{space 2} .0709268{col 41}{space 1}    1.03{col 50}{space 3}0.305{col 58}{space 4}-.0663056{col 71}{space 3} .2117225
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1493427{col 30}{space 2} .1424861{col 41}{space 1}    1.05{col 50}{space 3}0.295{col 58}{space 4}-.1299249{col 71}{space 3} .4286102
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1437924{col 30}{space 2} .0826649{col 41}{space 1}    1.74{col 50}{space 3}0.082{col 58}{space 4}-.0182279{col 71}{space 3} .3058126
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2191051{col 30}{space 2} .0573657{col 41}{space 1}    3.82{col 50}{space 3}0.000{col 58}{space 4} .1066704{col 71}{space 3} .3315398
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1838971{col 30}{space 2} .0453538{col 41}{space 1}   -4.05{col 50}{space 3}0.000{col 58}{space 4}-.2727889{col 71}{space 3}-.0950053
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0242383{col 30}{space 2}  .035089{col 41}{space 1}    0.69{col 50}{space 3}0.490{col 58}{space 4}-.0445348{col 71}{space 3} .0930114
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0276672{col 30}{space 2}  .062556{col 41}{space 1}    0.44{col 50}{space 3}0.658{col 58}{space 4}-.0949403{col 71}{space 3} .1502748
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0432632{col 30}{space 2} .3296729{col 41}{space 1}   -0.13{col 50}{space 3}0.896{col 58}{space 4}-.6894101{col 71}{space 3} .6028838
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7688173{col 30}{space 2} .1124624{col 41}{space 1}    6.84{col 50}{space 3}0.000{col 58}{space 4} .5483951{col 71}{space 3} .9892395
{txt}electricity_mean {c |}{col 18}{res}{space 2}  1.07918{col 30}{space 2} .1846259{col 41}{space 1}    5.85{col 50}{space 3}0.000{col 58}{space 4} .7173201{col 71}{space 3}  1.44104
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4892147{col 30}{space 2} .1196324{col 41}{space 1}    4.09{col 50}{space 3}0.000{col 58}{space 4} .2547395{col 71}{space 3} .7236899
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3649986{col 30}{space 2} .1044093{col 41}{space 1}    3.50{col 50}{space 3}0.000{col 58}{space 4} .1603602{col 71}{space 3} .5696369
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0013716{col 30}{space 2} .0302573{col 41}{space 1}   -0.05{col 50}{space 3}0.964{col 58}{space 4}-.0606748{col 71}{space 3} .0579316
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .2276827{col 30}{space 2} .0554796{col 41}{space 1}    4.10{col 50}{space 3}0.000{col 58}{space 4} .1189447{col 71}{space 3} .3364208
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0963473{col 30}{space 2} .0508531{col 41}{space 1}    1.89{col 50}{space 3}0.058{col 58}{space 4}-.0033229{col 71}{space 3} .1960175
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.800986{col 30}{space 2} .1528576{col 41}{space 1}   31.41{col 50}{space 3}0.000{col 58}{space 4} 4.501391{col 71}{space 3} 5.100581
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .68424012
         {txt}sigma_e {c |} {res} 1.2852961
             {txt}rho {c |} {res} .22082398{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,552
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,853

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0411                                         {txt}min = {res}         1
{txt}     between = {res}0.2587                                         {txt}avg = {res}       1.9
{txt}     overall = {res}0.1777                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}21{txt})     =  {res}  1119.25
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,853} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2435989{col 30}{space 2} .0353087{col 41}{space 1}    6.90{col 50}{space 3}0.000{col 58}{space 4} .1743952{col 71}{space 3} .3128027
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0081343{col 30}{space 2} .0071219{col 41}{space 1}    1.14{col 50}{space 3}0.253{col 58}{space 4}-.0058242{col 71}{space 3} .0220929
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0884741{col 30}{space 2} .1118585{col 41}{space 1}   -0.79{col 50}{space 3}0.429{col 58}{space 4}-.3077128{col 71}{space 3} .1307646
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0025595{col 30}{space 2} .0015753{col 41}{space 1}    1.62{col 50}{space 3}0.104{col 58}{space 4} -.000528{col 71}{space 3}  .005647
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0849337{col 30}{space 2} .0646931{col 41}{space 1}    1.31{col 50}{space 3}0.189{col 58}{space 4}-.0418623{col 71}{space 3} .2117298
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2937864{col 30}{space 2} .0495017{col 41}{space 1}    5.93{col 50}{space 3}0.000{col 58}{space 4} .1967648{col 71}{space 3} .3908079
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3058584{col 30}{space 2} .1105592{col 41}{space 1}    2.77{col 50}{space 3}0.006{col 58}{space 4} .0891663{col 71}{space 3} .5225505
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1035328{col 30}{space 2} .0783658{col 41}{space 1}    1.32{col 50}{space 3}0.186{col 58}{space 4}-.0500613{col 71}{space 3} .2571268
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3143832{col 30}{space 2}  .123581{col 41}{space 1}    2.54{col 50}{space 3}0.011{col 58}{space 4} .0721689{col 71}{space 3} .5565976
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1935791{col 30}{space 2} .0901182{col 41}{space 1}    2.15{col 50}{space 3}0.032{col 58}{space 4} .0169507{col 71}{space 3} .3702075
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1752686{col 30}{space 2} .0683668{col 41}{space 1}   -2.56{col 50}{space 3}0.010{col 58}{space 4}-.3092651{col 71}{space 3}-.0412721
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.134113{col 30}{space 2} .0483417{col 41}{space 1}   -2.77{col 50}{space 3}0.006{col 58}{space 4}-.2288609{col 71}{space 3}-.0393651
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0012742{col 30}{space 2} .0017733{col 41}{space 1}   -0.72{col 50}{space 3}0.472{col 58}{space 4}-.0047497{col 71}{space 3} .0022013
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1376061{col 30}{space 2}  .235055{col 41}{space 1}    0.59{col 50}{space 3}0.558{col 58}{space 4}-.3230932{col 71}{space 3} .5983054
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1003842{col 30}{space 2} .1393726{col 41}{space 1}    0.72{col 50}{space 3}0.471{col 58}{space 4}-.1727811{col 71}{space 3} .3735495
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4020696{col 30}{space 2} .1008988{col 41}{space 1}    3.98{col 50}{space 3}0.000{col 58}{space 4} .2043116{col 71}{space 3} .5998276
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4237193{col 30}{space 2} .1450242{col 41}{space 1}    2.92{col 50}{space 3}0.003{col 58}{space 4}  .139477{col 71}{space 3} .7079615
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2544306{col 30}{space 2} .1173563{col 41}{space 1}    2.17{col 50}{space 3}0.030{col 58}{space 4} .0244165{col 71}{space 3} .4844448
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}    .5231{col 30}{space 2} .0884854{col 41}{space 1}    5.91{col 50}{space 3}0.000{col 58}{space 4} .3496718{col 71}{space 3} .6965283
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2315874{col 30}{space 2} .0412735{col 41}{space 1}   -5.61{col 50}{space 3}0.000{col 58}{space 4}-.3124819{col 71}{space 3}-.1506928
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2760085{col 30}{space 2} .0407954{col 41}{space 1}    6.77{col 50}{space 3}0.000{col 58}{space 4} .1960511{col 71}{space 3} .3559659
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.459132{col 30}{space 2} .1280105{col 41}{space 1}   34.83{col 50}{space 3}0.000{col 58}{space 4} 4.208235{col 71}{space 3} 4.710028
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .55900642
         {txt}sigma_e {c |} {res} 1.3958609
             {txt}rho {c |} {res}  .1382131{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,014
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,108

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0645                                         {txt}min = {res}         1
{txt}     between = {res}0.3902                                         {txt}avg = {res}       3.6
{txt}     overall = {res}0.2394                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}   893.46
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,108} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0552278{col 30}{space 2} .0260511{col 41}{space 1}    2.12{col 50}{space 3}0.034{col 58}{space 4} .0041686{col 71}{space 3} .1062869
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0040426{col 30}{space 2} .0085383{col 41}{space 1}   -0.47{col 50}{space 3}0.636{col 58}{space 4}-.0207775{col 71}{space 3} .0126922
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}   .03483{col 30}{space 2} .1063589{col 41}{space 1}    0.33{col 50}{space 3}0.743{col 58}{space 4}-.1736296{col 71}{space 3} .2432896
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0061789{col 30}{space 2}  .002002{col 41}{space 1}    3.09{col 50}{space 3}0.002{col 58}{space 4}  .002255{col 71}{space 3} .0101029
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .171818{col 30}{space 2} .0754768{col 41}{space 1}    2.28{col 50}{space 3}0.023{col 58}{space 4} .0238861{col 71}{space 3} .3197498
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0686836{col 30}{space 2} .0514219{col 41}{space 1}    1.34{col 50}{space 3}0.182{col 58}{space 4}-.0321014{col 71}{space 3} .1694686
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0520301{col 30}{space 2} .0700828{col 41}{space 1}    0.74{col 50}{space 3}0.458{col 58}{space 4}-.0853297{col 71}{space 3} .1893898
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .197617{col 30}{space 2} .0678798{col 41}{space 1}    2.91{col 50}{space 3}0.004{col 58}{space 4} .0645751{col 71}{space 3} .3306589
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1140347{col 30}{space 2} .0877815{col 41}{space 1}    1.30{col 50}{space 3}0.194{col 58}{space 4}-.0580139{col 71}{space 3} .2860833
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2788642{col 30}{space 2}  .093833{col 41}{space 1}    2.97{col 50}{space 3}0.003{col 58}{space 4}  .094955{col 71}{space 3} .4627735
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2988109{col 30}{space 2} .0667718{col 41}{space 1}    4.48{col 50}{space 3}0.000{col 58}{space 4} .1679404{col 71}{space 3} .4296813
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0316423{col 30}{space 2} .0897667{col 41}{space 1}    0.35{col 50}{space 3}0.724{col 58}{space 4}-.1442972{col 71}{space 3} .2075818
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} -.005346{col 30}{space 2} .0128633{col 41}{space 1}   -0.42{col 50}{space 3}0.678{col 58}{space 4}-.0305576{col 71}{space 3} .0198657
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}   .15329{col 30}{space 2} .1175442{col 41}{space 1}    1.30{col 50}{space 3}0.192{col 58}{space 4}-.0770924{col 71}{space 3} .3836724
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0827971{col 30}{space 2} .1141401{col 41}{space 1}   -0.73{col 50}{space 3}0.468{col 58}{space 4}-.3065075{col 71}{space 3} .1409133
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .9771175{col 30}{space 2} .1291708{col 41}{space 1}    7.56{col 50}{space 3}0.000{col 58}{space 4} .7239474{col 71}{space 3} 1.230288
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8233208{col 30}{space 2} .1240664{col 41}{space 1}    6.64{col 50}{space 3}0.000{col 58}{space 4} .5801552{col 71}{space 3} 1.066486
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0476658{col 30}{space 2}  .146033{col 41}{space 1}    0.33{col 50}{space 3}0.744{col 58}{space 4}-.2385537{col 71}{space 3} .3338853
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0615651{col 30}{space 2} .1071329{col 41}{space 1}   -0.57{col 50}{space 3}0.566{col 58}{space 4}-.2715418{col 71}{space 3} .1484117
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0410523{col 30}{space 2} .0419989{col 41}{space 1}   -0.98{col 50}{space 3}0.328{col 58}{space 4}-.1233687{col 71}{space 3}  .041264
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5834235{col 30}{space 2} .0613207{col 41}{space 1}   -9.51{col 50}{space 3}0.000{col 58}{space 4}-.7036097{col 71}{space 3}-.4632372
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}  -.48089{col 30}{space 2} .0575961{col 41}{space 1}   -8.35{col 50}{space 3}0.000{col 58}{space 4}-.5937763{col 71}{space 3}-.3680037
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3852028{col 30}{space 2} .0559497{col 41}{space 1}   -6.88{col 50}{space 3}0.000{col 58}{space 4}-.4948621{col 71}{space 3}-.2755434
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.352066{col 30}{space 2} .1776232{col 41}{space 1}   24.50{col 50}{space 3}0.000{col 58}{space 4} 4.003931{col 71}{space 3} 4.700201
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .70800298
         {txt}sigma_e {c |} {res} 1.2410842
             {txt}rho {c |} {res} .24553216{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     1,113
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}       271

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0639                                         {txt}min = {res}         1
{txt}     between = {res}0.3886                                         {txt}avg = {res}       4.1
{txt}     overall = {res}0.2686                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}23{txt})     =  {res}   303.23
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:271} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1926865{col 30}{space 2} .0331565{col 41}{space 1}    5.81{col 50}{space 3}0.000{col 58}{space 4}  .127701{col 71}{space 3}  .257672
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0491125{col 30}{space 2} .0207535{col 41}{space 1}   -2.37{col 50}{space 3}0.018{col 58}{space 4}-.0897887{col 71}{space 3}-.0084363
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .3383112{col 30}{space 2} .2166852{col 41}{space 1}    1.56{col 50}{space 3}0.118{col 58}{space 4} -.086384{col 71}{space 3} .7630065
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0070107{col 30}{space 2} .0039558{col 41}{space 1}   -1.77{col 50}{space 3}0.076{col 58}{space 4} -.014764{col 71}{space 3} .0007426
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3478125{col 30}{space 2} .1299211{col 41}{space 1}    2.68{col 50}{space 3}0.007{col 58}{space 4} .0931719{col 71}{space 3} .6024532
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1507063{col 30}{space 2} .1256324{col 41}{space 1}    1.20{col 50}{space 3}0.230{col 58}{space 4}-.0955287{col 71}{space 3} .3969414
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2306698{col 30}{space 2} .1789074{col 41}{space 1}    1.29{col 50}{space 3}0.197{col 58}{space 4}-.1199823{col 71}{space 3} .5813218
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2249758{col 30}{space 2} .1190841{col 41}{space 1}    1.89{col 50}{space 3}0.059{col 58}{space 4}-.0084247{col 71}{space 3} .4583762
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} -.022725{col 30}{space 2} .1227961{col 41}{space 1}   -0.19{col 50}{space 3}0.853{col 58}{space 4}-.2634008{col 71}{space 3} .2179509
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0576011{col 30}{space 2} .0942764{col 41}{space 1}    0.61{col 50}{space 3}0.541{col 58}{space 4}-.1271773{col 71}{space 3} .2423795
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2558709{col 30}{space 2}  .103951{col 41}{space 1}    2.46{col 50}{space 3}0.014{col 58}{space 4} .0521307{col 71}{space 3} .4596111
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1968003{col 30}{space 2} .1089714{col 41}{space 1}   -1.81{col 50}{space 3}0.071{col 58}{space 4}-.4103804{col 71}{space 3} .0167797
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0031638{col 30}{space 2} .0138893{col 41}{space 1}   -0.23{col 50}{space 3}0.820{col 58}{space 4}-.0303863{col 71}{space 3} .0240588
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0167234{col 30}{space 2} .0962313{col 41}{space 1}    0.17{col 50}{space 3}0.862{col 58}{space 4}-.1718865{col 71}{space 3} .2053334
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .7060766{col 30}{space 2} .3325583{col 41}{space 1}    2.12{col 50}{space 3}0.034{col 58}{space 4} .0542743{col 71}{space 3} 1.357879
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7249204{col 30}{space 2} .2390391{col 41}{space 1}    3.03{col 50}{space 3}0.002{col 58}{space 4} .2564125{col 71}{space 3} 1.193428
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.188559{col 30}{space 2} .2427675{col 41}{space 1}    4.90{col 50}{space 3}0.000{col 58}{space 4} .7127437{col 71}{space 3} 1.664375
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1293937{col 30}{space 2} .2101316{col 41}{space 1}   -0.62{col 50}{space 3}0.538{col 58}{space 4}-.5412442{col 71}{space 3} .2824567
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1914066{col 30}{space 2} .2224053{col 41}{space 1}    0.86{col 50}{space 3}0.389{col 58}{space 4}-.2444999{col 71}{space 3}  .627313
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0387718{col 30}{space 2} .0578475{col 41}{space 1}   -0.67{col 50}{space 3}0.503{col 58}{space 4}-.1521509{col 71}{space 3} .0746073
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.0582123{col 30}{space 2} .1091239{col 41}{space 1}   -0.53{col 50}{space 3}0.594{col 58}{space 4}-.2720912{col 71}{space 3} .1556665
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0611724{col 30}{space 2} .0895041{col 41}{space 1}   -0.68{col 50}{space 3}0.494{col 58}{space 4}-.2365972{col 71}{space 3} .1142525
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .1341771{col 30}{space 2} .0972178{col 41}{space 1}    1.38{col 50}{space 3}0.168{col 58}{space 4}-.0563662{col 71}{space 3} .3247204
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.404136{col 30}{space 2}  .359103{col 41}{space 1}   12.26{col 50}{space 3}0.000{col 58}{space 4} 3.700307{col 71}{space 3} 5.107965
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .78177684
         {txt}sigma_e {c |} {res} 1.1384368
             {txt}rho {c |} {res} .32045447{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     6,588
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,089

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0717                                         {txt}min = {res}         1
{txt}     between = {res}0.3029                                         {txt}avg = {res}       6.0
{txt}     overall = {res}0.1834                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}25{txt})     =  {res}   929.90
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,089} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1032792{col 30}{space 2} .0159098{col 41}{space 1}    6.49{col 50}{space 3}0.000{col 58}{space 4} .0720965{col 71}{space 3}  .134462
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0046355{col 30}{space 2}  .008588{col 41}{space 1}   -0.54{col 50}{space 3}0.589{col 58}{space 4}-.0214677{col 71}{space 3} .0121967
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1241959{col 30}{space 2} .0911563{col 41}{space 1}    1.36{col 50}{space 3}0.173{col 58}{space 4}-.0544672{col 71}{space 3} .3028589
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0001475{col 30}{space 2} .0018636{col 41}{space 1}    0.08{col 50}{space 3}0.937{col 58}{space 4}-.0035051{col 71}{space 3} .0038001
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0118797{col 30}{space 2} .0562916{col 41}{space 1}    0.21{col 50}{space 3}0.833{col 58}{space 4}-.0984498{col 71}{space 3} .1222093
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2838324{col 30}{space 2} .0515584{col 41}{space 1}    5.51{col 50}{space 3}0.000{col 58}{space 4} .1827799{col 71}{space 3}  .384885
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1778431{col 30}{space 2} .0752543{col 41}{space 1}    2.36{col 50}{space 3}0.018{col 58}{space 4} .0303473{col 71}{space 3} .3253389
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2997498{col 30}{space 2} .0515984{col 41}{space 1}    5.81{col 50}{space 3}0.000{col 58}{space 4} .1986189{col 71}{space 3} .4008807
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .356807{col 30}{space 2} .0522553{col 41}{space 1}    6.83{col 50}{space 3}0.000{col 58}{space 4} .2543886{col 71}{space 3} .4592254
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0325488{col 30}{space 2} .0421163{col 41}{space 1}    0.77{col 50}{space 3}0.440{col 58}{space 4}-.0499977{col 71}{space 3} .1150952
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .177541{col 30}{space 2} .0445601{col 41}{space 1}    3.98{col 50}{space 3}0.000{col 58}{space 4} .0902048{col 71}{space 3} .2648772
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0068639{col 30}{space 2} .0362491{col 41}{space 1}   -0.19{col 50}{space 3}0.850{col 58}{space 4}-.0779109{col 71}{space 3} .0641831
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0009804{col 30}{space 2} .0015628{col 41}{space 1}    0.63{col 50}{space 3}0.530{col 58}{space 4}-.0020826{col 71}{space 3} .0040434
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0345049{col 30}{space 2} .0412183{col 41}{space 1}   -0.84{col 50}{space 3}0.403{col 58}{space 4}-.1152912{col 71}{space 3} .0462814
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .166739{col 30}{space 2} .1433737{col 41}{space 1}    1.16{col 50}{space 3}0.245{col 58}{space 4}-.1142683{col 71}{space 3} .4477463
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .2696633{col 30}{space 2} .1092768{col 41}{space 1}    2.47{col 50}{space 3}0.014{col 58}{space 4} .0554847{col 71}{space 3} .4838418
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5248564{col 30}{space 2} .1358706{col 41}{space 1}    3.86{col 50}{space 3}0.000{col 58}{space 4}  .258555{col 71}{space 3} .7911579
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1599671{col 30}{space 2} .0999347{col 41}{space 1}    1.60{col 50}{space 3}0.109{col 58}{space 4}-.0359014{col 71}{space 3} .3558356
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3345095{col 30}{space 2}  .092722{col 41}{space 1}    3.61{col 50}{space 3}0.000{col 58}{space 4} .1527778{col 71}{space 3} .5162412
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0202097{col 30}{space 2} .0314787{col 41}{space 1}    0.64{col 50}{space 3}0.521{col 58}{space 4}-.0414873{col 71}{space 3} .0819067
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1379931{col 30}{space 2} .0570797{col 41}{space 1}   -2.42{col 50}{space 3}0.016{col 58}{space 4}-.2498673{col 71}{space 3}-.0261189
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.1494229{col 30}{space 2} .0491372{col 41}{space 1}   -3.04{col 50}{space 3}0.002{col 58}{space 4}  -.24573{col 71}{space 3}-.0531158
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}  .344422{col 30}{space 2} .0490458{col 41}{space 1}    7.02{col 50}{space 3}0.000{col 58}{space 4} .2482941{col 71}{space 3}   .44055
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1291085{col 30}{space 2} .0490409{col 41}{space 1}    2.63{col 50}{space 3}0.008{col 58}{space 4} .0329901{col 71}{space 3} .2252268
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .3559957{col 30}{space 2} .0482836{col 41}{space 1}    7.37{col 50}{space 3}0.000{col 58}{space 4} .2613617{col 71}{space 3} .4506297
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  3.94759{col 30}{space 2} .1741001{col 41}{space 1}   22.67{col 50}{space 3}0.000{col 58}{space 4} 3.606361{col 71}{space 3}  4.28882
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .70356252
         {txt}sigma_e {c |} {res} 1.2219867
             {txt}rho {c |} {res} .24896254{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. 
. 
. esttab using  S15_balance.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean _cons )
{res}{txt}(note: file S15_balance.rtf not found)
(output written to {browse  `"S15_balance.rtf"'})

{com}. 
. 
. 
. 
. 
. *                          vill_village_level                                  *
. 
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill i.country i.year   , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    30,867
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     9,851

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0307                                         {txt}min = {res}         1
{txt}     between = {res}0.4920                                         {txt}avg = {res}       3.1
{txt}     overall = {res}0.3332                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 11441.55
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:9,851} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0496349{col 30}{space 2} .0095502{col 41}{space 1}    5.20{col 50}{space 3}0.000{col 58}{space 4} .0309169{col 71}{space 3} .0683528
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0468484{col 30}{space 2}  .003462{col 41}{space 1}  -13.53{col 50}{space 3}0.000{col 58}{space 4}-.0536338{col 71}{space 3}-.0400631
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0120667{col 30}{space 2} .0036976{col 41}{space 1}    3.26{col 50}{space 3}0.001{col 58}{space 4} .0048197{col 71}{space 3} .0193138
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0319224{col 30}{space 2} .0406579{col 41}{space 1}   -0.79{col 50}{space 3}0.432{col 58}{space 4}-.1116104{col 71}{space 3} .0477655
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0008766{col 30}{space 2} .0007008{col 41}{space 1}   -1.25{col 50}{space 3}0.211{col 58}{space 4}-.0022501{col 71}{space 3} .0004969
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0334698{col 30}{space 2} .0250618{col 41}{space 1}   -1.34{col 50}{space 3}0.182{col 58}{space 4}  -.08259{col 71}{space 3} .0156504
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2650137{col 30}{space 2} .0208504{col 41}{space 1}   12.71{col 50}{space 3}0.000{col 58}{space 4} .2241475{col 71}{space 3} .3058798
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1375562{col 30}{space 2} .0430776{col 41}{space 1}    3.19{col 50}{space 3}0.001{col 58}{space 4} .0531256{col 71}{space 3} .2219868
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1609082{col 30}{space 2} .0254931{col 41}{space 1}    6.31{col 50}{space 3}0.000{col 58}{space 4} .1109426{col 71}{space 3} .2108739
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .142107{col 30}{space 2} .0310236{col 41}{space 1}    4.58{col 50}{space 3}0.000{col 58}{space 4} .0813019{col 71}{space 3}  .202912
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1118783{col 30}{space 2} .0289253{col 41}{space 1}    3.87{col 50}{space 3}0.000{col 58}{space 4} .0551858{col 71}{space 3} .1685708
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1590837{col 30}{space 2} .0246596{col 41}{space 1}    6.45{col 50}{space 3}0.000{col 58}{space 4} .1107519{col 71}{space 3} .2074156
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0771998{col 30}{space 2} .0191821{col 41}{space 1}   -4.02{col 50}{space 3}0.000{col 58}{space 4} -.114796{col 71}{space 3}-.0396035
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0009818{col 30}{space 2} .0013521{col 41}{space 1}    0.73{col 50}{space 3}0.468{col 58}{space 4}-.0016683{col 71}{space 3} .0036318
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1482686{col 30}{space 2} .0223646{col 41}{space 1}    6.63{col 50}{space 3}0.000{col 58}{space 4} .1044348{col 71}{space 3} .1921025
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0454415{col 30}{space 2} .0636147{col 41}{space 1}    0.71{col 50}{space 3}0.475{col 58}{space 4} -.079241{col 71}{space 3} .1701239
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4918543{col 30}{space 2} .0406957{col 41}{space 1}   12.09{col 50}{space 3}0.000{col 58}{space 4} .4120923{col 71}{space 3} .5716164
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5703292{col 30}{space 2} .0478061{col 41}{space 1}   11.93{col 50}{space 3}0.000{col 58}{space 4}  .476631{col 71}{space 3} .6640273
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2552407{col 30}{space 2} .0492989{col 41}{space 1}    5.18{col 50}{space 3}0.000{col 58}{space 4} .1586167{col 71}{space 3} .3518648
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1658839{col 30}{space 2} .0375613{col 41}{space 1}    4.42{col 50}{space 3}0.000{col 58}{space 4} .0922651{col 71}{space 3} .2395027
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .0885968{col 30}{space 2} .0128044{col 41}{space 1}    6.92{col 50}{space 3}0.000{col 58}{space 4} .0635006{col 71}{space 3}  .113693
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.6873771{col 30}{space 2} .0520467{col 41}{space 1}  -13.21{col 50}{space 3}0.000{col 58}{space 4}-.7893867{col 71}{space 3}-.5853675
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.820031{col 30}{space 2} .0458938{col 41}{space 1}  -39.66{col 50}{space 3}0.000{col 58}{space 4}-1.909981{col 71}{space 3} -1.73008
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.8339328{col 30}{space 2}  .049884{col 41}{space 1}  -16.72{col 50}{space 3}0.000{col 58}{space 4}-.9317035{col 71}{space 3} -.736162
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.7102672{col 30}{space 2}  .075507{col 41}{space 1}   -9.41{col 50}{space 3}0.000{col 58}{space 4}-.8582583{col 71}{space 3}-.5622762
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .1457978{col 30}{space 2} .0524085{col 41}{space 1}    2.78{col 50}{space 3}0.005{col 58}{space 4} .0430789{col 71}{space 3} .2485166
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.1789263{col 30}{space 2} .1000728{col 41}{space 1}   -1.79{col 50}{space 3}0.074{col 58}{space 4}-.3750654{col 71}{space 3} .0172128
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .1061261{col 30}{space 2} .0914193{col 41}{space 1}    1.16{col 50}{space 3}0.246{col 58}{space 4}-.0730524{col 71}{space 3} .2853046
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0885517{col 30}{space 2} .0919775{col 41}{space 1}    0.96{col 50}{space 3}0.336{col 58}{space 4} -.091721{col 71}{space 3} .2688244
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .1163666{col 30}{space 2} .0945221{col 41}{space 1}    1.23{col 50}{space 3}0.218{col 58}{space 4}-.0688934{col 71}{space 3} .3016265
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1185725{col 30}{space 2} .0924219{col 41}{space 1}    1.28{col 50}{space 3}0.200{col 58}{space 4}-.0625711{col 71}{space 3} .2997161
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.1469897{col 30}{space 2} .0947497{col 41}{space 1}   -1.55{col 50}{space 3}0.121{col 58}{space 4}-.3326958{col 71}{space 3} .0387164
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .2905722{col 30}{space 2} .0927748{col 41}{space 1}    3.13{col 50}{space 3}0.002{col 58}{space 4} .1087369{col 71}{space 3} .4724074
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.1718703{col 30}{space 2} .1026016{col 41}{space 1}   -1.68{col 50}{space 3}0.094{col 58}{space 4}-.3729658{col 71}{space 3} .0292251
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .5781316{col 30}{space 2} .0955773{col 41}{space 1}    6.05{col 50}{space 3}0.000{col 58}{space 4} .3908034{col 71}{space 3} .7654598
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .1502447{col 30}{space 2} .0938588{col 41}{space 1}    1.60{col 50}{space 3}0.109{col 58}{space 4}-.0337152{col 71}{space 3} .3342046
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.747257{col 30}{space 2} .1172314{col 41}{space 1}   40.49{col 50}{space 3}0.000{col 58}{space 4} 4.517487{col 71}{space 3} 4.977026
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}   .699446
         {txt}sigma_e {c |} {res} 1.2204085
             {txt}rho {c |} {res} .24725531{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,299
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,149

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0226                                         {txt}min = {res}         1
{txt}     between = {res}0.3171                                         {txt}avg = {res}       3.0
{txt}     overall = {res}0.2003                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1693.29
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,149} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2}   .05153{col 30}{space 2} .0158312{col 41}{space 1}    3.25{col 50}{space 3}0.001{col 58}{space 4} .0205014{col 71}{space 3} .0825585
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0258899{col 30}{space 2} .0101683{col 41}{space 1}   -2.55{col 50}{space 3}0.011{col 58}{space 4}-.0458194{col 71}{space 3}-.0059603
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0524388{col 30}{space 2} .0076637{col 41}{space 1}    6.84{col 50}{space 3}0.000{col 58}{space 4} .0374181{col 71}{space 3} .0674595
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0502079{col 30}{space 2} .0646734{col 41}{space 1}   -0.78{col 50}{space 3}0.438{col 58}{space 4}-.1769654{col 71}{space 3} .0765496
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0026494{col 30}{space 2} .0010973{col 41}{space 1}   -2.41{col 50}{space 3}0.016{col 58}{space 4}-.0048001{col 71}{space 3}-.0004988
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} -.028153{col 30}{space 2} .0409127{col 41}{space 1}   -0.69{col 50}{space 3}0.491{col 58}{space 4}-.1083405{col 71}{space 3} .0520345
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3045142{col 30}{space 2} .0334856{col 41}{space 1}    9.09{col 50}{space 3}0.000{col 58}{space 4} .2388836{col 71}{space 3} .3701448
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2478863{col 30}{space 2} .1585173{col 41}{space 1}   -1.56{col 50}{space 3}0.118{col 58}{space 4}-.5585745{col 71}{space 3} .0628019
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1964392{col 30}{space 2} .0389563{col 41}{space 1}    5.04{col 50}{space 3}0.000{col 58}{space 4} .1200863{col 71}{space 3} .2727921
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1283005{col 30}{space 2} .0483015{col 41}{space 1}    2.66{col 50}{space 3}0.008{col 58}{space 4} .0336313{col 71}{space 3} .2229696
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0690089{col 30}{space 2}  .072196{col 41}{space 1}    0.96{col 50}{space 3}0.339{col 58}{space 4}-.0724926{col 71}{space 3} .2105105
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1935484{col 30}{space 2} .0523047{col 41}{space 1}    3.70{col 50}{space 3}0.000{col 58}{space 4} .0910331{col 71}{space 3} .2960637
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1150559{col 30}{space 2} .0313309{col 41}{space 1}   -3.67{col 50}{space 3}0.000{col 58}{space 4}-.1764633{col 71}{space 3}-.0536484
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0144732{col 30}{space 2} .0039291{col 41}{space 1}    3.68{col 50}{space 3}0.000{col 58}{space 4} .0067724{col 71}{space 3} .0221741
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1971195{col 30}{space 2} .0327584{col 41}{space 1}    6.02{col 50}{space 3}0.000{col 58}{space 4} .1329142{col 71}{space 3} .2613248
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} 1.071872{col 30}{space 2} .2935056{col 41}{space 1}    3.65{col 50}{space 3}0.000{col 58}{space 4} .4966119{col 71}{space 3} 1.647133
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4083193{col 30}{space 2} .0617966{col 41}{space 1}    6.61{col 50}{space 3}0.000{col 58}{space 4} .2872002{col 71}{space 3} .5294384
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .341302{col 30}{space 2} .0761745{col 41}{space 1}    4.48{col 50}{space 3}0.000{col 58}{space 4} .1920028{col 71}{space 3} .4906012
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4987224{col 30}{space 2} .1318778{col 41}{space 1}    3.78{col 50}{space 3}0.000{col 58}{space 4} .2402466{col 71}{space 3} .7571982
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1065931{col 30}{space 2} .0691072{col 41}{space 1}    1.54{col 50}{space 3}0.123{col 58}{space 4}-.0288545{col 71}{space 3} .2420406
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .1363006{col 30}{space 2} .0199873{col 41}{space 1}    6.82{col 50}{space 3}0.000{col 58}{space 4} .0971263{col 71}{space 3}  .175475
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1866489{col 30}{space 2} .0237571{col 41}{space 1}   -7.86{col 50}{space 3}0.000{col 58}{space 4} -.233212{col 71}{space 3}-.1400858
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.508871{col 30}{space 2} .1400789{col 41}{space 1}   17.91{col 50}{space 3}0.000{col 58}{space 4} 2.234321{col 71}{space 3} 2.783421
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .65675611
         {txt}sigma_e {c |} {res} 1.0654634
             {txt}rho {c |} {res} .27533824{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_MALAWI  if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,301
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,381

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0212                                         {txt}min = {res}         1
{txt}     between = {res}0.4069                                         {txt}avg = {res}       3.1
{txt}     overall = {res}0.2748                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1393.17
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,381} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0696823{col 30}{space 2}  .026349{col 41}{space 1}    2.64{col 50}{space 3}0.008{col 58}{space 4} .0180391{col 71}{space 3} .1213255
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0347837{col 30}{space 2} .0106975{col 41}{space 1}   -3.25{col 50}{space 3}0.001{col 58}{space 4}-.0557503{col 71}{space 3}-.0138171
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0039923{col 30}{space 2} .0116361{col 41}{space 1}    0.34{col 50}{space 3}0.732{col 58}{space 4} -.018814{col 71}{space 3} .0267986
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2620466{col 30}{space 2} .1069189{col 41}{space 1}   -2.45{col 50}{space 3}0.014{col 58}{space 4}-.4716038{col 71}{space 3}-.0524894
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.001547{col 30}{space 2} .0018198{col 41}{space 1}   -0.85{col 50}{space 3}0.395{col 58}{space 4}-.0051137{col 71}{space 3} .0020196
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1081432{col 30}{space 2}  .062713{col 41}{space 1}   -1.72{col 50}{space 3}0.085{col 58}{space 4}-.2310584{col 71}{space 3}  .014772
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3092835{col 30}{space 2} .0603715{col 41}{space 1}    5.12{col 50}{space 3}0.000{col 58}{space 4} .1909575{col 71}{space 3} .4276095
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2035583{col 30}{space 2} .1980441{col 41}{space 1}    1.03{col 50}{space 3}0.304{col 58}{space 4}-.1846011{col 71}{space 3} .5917177
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0739987{col 30}{space 2} .0711631{col 41}{space 1}    1.04{col 50}{space 3}0.298{col 58}{space 4}-.0654784{col 71}{space 3} .2134758
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1193938{col 30}{space 2} .1438545{col 41}{space 1}    0.83{col 50}{space 3}0.407{col 58}{space 4}-.1625558{col 71}{space 3} .4013434
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1293708{col 30}{space 2} .0834192{col 41}{space 1}    1.55{col 50}{space 3}0.121{col 58}{space 4}-.0341277{col 71}{space 3} .2928694
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2318233{col 30}{space 2} .0575611{col 41}{space 1}    4.03{col 50}{space 3}0.000{col 58}{space 4} .1190057{col 71}{space 3} .3446409
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1530463{col 30}{space 2} .0453862{col 41}{space 1}   -3.37{col 50}{space 3}0.001{col 58}{space 4}-.2420015{col 71}{space 3} -.064091
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .1072994{col 30}{space 2} .0399703{col 41}{space 1}    2.68{col 50}{space 3}0.007{col 58}{space 4}  .028959{col 71}{space 3} .1856397
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0885109{col 30}{space 2} .0637245{col 41}{space 1}    1.39{col 50}{space 3}0.165{col 58}{space 4}-.0363869{col 71}{space 3} .2134086
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1022031{col 30}{space 2} .3407084{col 41}{space 1}    0.30{col 50}{space 3}0.764{col 58}{space 4}-.5655731{col 71}{space 3} .7699792
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .732267{col 30}{space 2}  .113833{col 41}{space 1}    6.43{col 50}{space 3}0.000{col 58}{space 4} .5091585{col 71}{space 3} .9553755
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8649135{col 30}{space 2} .1857279{col 41}{space 1}    4.66{col 50}{space 3}0.000{col 58}{space 4} .5008935{col 71}{space 3} 1.228934
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3374965{col 30}{space 2} .1214088{col 41}{space 1}    2.78{col 50}{space 3}0.005{col 58}{space 4} .0995396{col 71}{space 3} .5754535
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2640918{col 30}{space 2} .1051241{col 41}{space 1}    2.51{col 50}{space 3}0.012{col 58}{space 4} .0580523{col 71}{space 3} .4701312
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0493586{col 30}{space 2} .0416546{col 41}{space 1}   -1.18{col 50}{space 3}0.236{col 58}{space 4}    -.131{col 71}{space 3} .0322829
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .3023584{col 30}{space 2} .0636465{col 41}{space 1}    4.75{col 50}{space 3}0.000{col 58}{space 4} .1776136{col 71}{space 3} .4271032
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .1144779{col 30}{space 2} .0515365{col 41}{space 1}    2.22{col 50}{space 3}0.026{col 58}{space 4} .0134682{col 71}{space 3} .2154876
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.321578{col 30}{space 2} .2292198{col 41}{space 1}   23.22{col 50}{space 3}0.000{col 58}{space 4} 4.872315{col 71}{space 3}  5.77084
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .68913216
         {txt}sigma_e {c |} {res} 1.2903371
             {txt}rho {c |} {res} .22193054{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,552
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,853

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0248                                         {txt}min = {res}         1
{txt}     between = {res}0.2819                                         {txt}avg = {res}       1.9
{txt}     overall = {res}0.1865                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1204.48
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,853} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .1113506{col 30}{space 2} .0309772{col 41}{space 1}    3.59{col 50}{space 3}0.000{col 58}{space 4} .0506365{col 71}{space 3} .1720647
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0612155{col 30}{space 2} .0069877{col 41}{space 1}   -8.76{col 50}{space 3}0.000{col 58}{space 4}-.0749111{col 71}{space 3}-.0475199
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0151268{col 30}{space 2} .0068313{col 41}{space 1}    2.21{col 50}{space 3}0.027{col 58}{space 4} .0017377{col 71}{space 3} .0285159
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0550708{col 30}{space 2} .1111892{col 41}{space 1}   -0.50{col 50}{space 3}0.620{col 58}{space 4}-.2729976{col 71}{space 3} .1628559
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0012734{col 30}{space 2} .0015677{col 41}{space 1}    0.81{col 50}{space 3}0.417{col 58}{space 4}-.0017993{col 71}{space 3}  .004346
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0358693{col 30}{space 2} .0633392{col 41}{space 1}    0.57{col 50}{space 3}0.571{col 58}{space 4}-.0882733{col 71}{space 3} .1600118
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2885735{col 30}{space 2} .0492115{col 41}{space 1}    5.86{col 50}{space 3}0.000{col 58}{space 4} .1921208{col 71}{space 3} .3850263
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3308213{col 30}{space 2} .1118729{col 41}{space 1}    2.96{col 50}{space 3}0.003{col 58}{space 4} .1115545{col 71}{space 3} .5500882
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1170264{col 30}{space 2} .0793293{col 41}{space 1}    1.48{col 50}{space 3}0.140{col 58}{space 4}-.0384562{col 71}{space 3} .2725091
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2412483{col 30}{space 2}  .125754{col 41}{space 1}    1.92{col 50}{space 3}0.055{col 58}{space 4}-.0052251{col 71}{space 3} .4877216
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2052991{col 30}{space 2} .0909244{col 41}{space 1}    2.26{col 50}{space 3}0.024{col 58}{space 4} .0270907{col 71}{space 3} .3835076
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1625505{col 30}{space 2} .0696389{col 41}{space 1}   -2.33{col 50}{space 3}0.020{col 58}{space 4}-.2990402{col 71}{space 3}-.0260608
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0742205{col 30}{space 2} .0485068{col 41}{space 1}   -1.53{col 50}{space 3}0.126{col 58}{space 4}-.1692921{col 71}{space 3}  .020851
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0007428{col 30}{space 2} .0017112{col 41}{space 1}   -0.43{col 50}{space 3}0.664{col 58}{space 4}-.0040967{col 71}{space 3} .0026112
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2308628{col 30}{space 2} .2376983{col 41}{space 1}    0.97{col 50}{space 3}0.331{col 58}{space 4}-.2350174{col 71}{space 3} .6967429
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0501335{col 30}{space 2} .1401088{col 41}{space 1}    0.36{col 50}{space 3}0.720{col 58}{space 4}-.2244747{col 71}{space 3} .3247418
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .2014994{col 30}{space 2} .1030178{col 41}{space 1}    1.96{col 50}{space 3}0.050{col 58}{space 4}-.0004118{col 71}{space 3} .4034105
{txt}electricity_mean {c |}{col 18}{res}{space 2} .2243951{col 30}{space 2} .1501461{col 41}{space 1}    1.49{col 50}{space 3}0.135{col 58}{space 4}-.0698859{col 71}{space 3}  .518676
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0906865{col 30}{space 2} .1177991{col 41}{space 1}    0.77{col 50}{space 3}0.441{col 58}{space 4}-.1401955{col 71}{space 3} .3215686
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4216338{col 30}{space 2} .0899491{col 41}{space 1}    4.69{col 50}{space 3}0.000{col 58}{space 4} .2453368{col 71}{space 3} .5979309
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0287149{col 30}{space 2} .0365319{col 41}{space 1}   -0.79{col 50}{space 3}0.432{col 58}{space 4}-.1003162{col 71}{space 3} .0428863
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}  .301318{col 30}{space 2} .0418771{col 41}{space 1}    7.20{col 50}{space 3}0.000{col 58}{space 4} .2192403{col 71}{space 3} .3833956
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.137507{col 30}{space 2} .1547286{col 41}{space 1}   33.20{col 50}{space 3}0.000{col 58}{space 4} 4.834245{col 71}{space 3}  5.44077
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .50647991
         {txt}sigma_e {c |} {res} 1.4060479
             {txt}rho {c |} {res} .11485236{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,014
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,108

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0689                                         {txt}min = {res}         1
{txt}     between = {res}0.4305                                         {txt}avg = {res}       3.6
{txt}     overall = {res}0.2663                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1049.42
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,108} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .1057641{col 30}{space 2} .0261953{col 41}{space 1}    4.04{col 50}{space 3}0.000{col 58}{space 4} .0544223{col 71}{space 3} .1571059
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.1077186{col 30}{space 2} .0138014{col 41}{space 1}   -7.80{col 50}{space 3}0.000{col 58}{space 4}-.1347688{col 71}{space 3}-.0806685
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}  .005232{col 30}{space 2}  .008349{col 41}{space 1}    0.63{col 50}{space 3}0.531{col 58}{space 4}-.0111319{col 71}{space 3} .0215958
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0037442{col 30}{space 2} .1049752{col 41}{space 1}   -0.04{col 50}{space 3}0.972{col 58}{space 4}-.2094918{col 71}{space 3} .2020034
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0041769{col 30}{space 2} .0019611{col 41}{space 1}    2.13{col 50}{space 3}0.033{col 58}{space 4} .0003333{col 71}{space 3} .0080205
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1041203{col 30}{space 2} .0751335{col 41}{space 1}    1.39{col 50}{space 3}0.166{col 58}{space 4}-.0431386{col 71}{space 3} .2513793
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0431769{col 30}{space 2} .0509819{col 41}{space 1}    0.85{col 50}{space 3}0.397{col 58}{space 4}-.0567459{col 71}{space 3} .1430997
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0548315{col 30}{space 2} .0695136{col 41}{space 1}    0.79{col 50}{space 3}0.430{col 58}{space 4}-.0814127{col 71}{space 3} .1910757
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1787009{col 30}{space 2} .0676605{col 41}{space 1}    2.64{col 50}{space 3}0.008{col 58}{space 4} .0460888{col 71}{space 3}  .311313
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1031605{col 30}{space 2} .0872686{col 41}{space 1}    1.18{col 50}{space 3}0.237{col 58}{space 4}-.0678829{col 71}{space 3} .2742038
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2603552{col 30}{space 2} .0934665{col 41}{space 1}    2.79{col 50}{space 3}0.005{col 58}{space 4} .0771642{col 71}{space 3} .4435463
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2918357{col 30}{space 2} .0667943{col 41}{space 1}    4.37{col 50}{space 3}0.000{col 58}{space 4} .1609212{col 71}{space 3} .4227502
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}  .055292{col 30}{space 2} .0890916{col 41}{space 1}    0.62{col 50}{space 3}0.535{col 58}{space 4}-.1193243{col 71}{space 3} .2299083
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0042484{col 30}{space 2} .0130049{col 41}{space 1}    0.33{col 50}{space 3}0.744{col 58}{space 4}-.0212407{col 71}{space 3} .0297375
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1763307{col 30}{space 2} .1188837{col 41}{space 1}    1.48{col 50}{space 3}0.138{col 58}{space 4} -.056677{col 71}{space 3} .4093384
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0014437{col 30}{space 2} .1104401{col 41}{space 1}   -0.01{col 50}{space 3}0.990{col 58}{space 4}-.2179024{col 71}{space 3}  .215015
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .8210158{col 30}{space 2} .1294203{col 41}{space 1}    6.34{col 50}{space 3}0.000{col 58}{space 4} .5673567{col 71}{space 3} 1.074675
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7167607{col 30}{space 2} .1183728{col 41}{space 1}    6.06{col 50}{space 3}0.000{col 58}{space 4} .4847542{col 71}{space 3} .9487671
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0154741{col 30}{space 2} .1429362{col 41}{space 1}    0.11{col 50}{space 3}0.914{col 58}{space 4}-.2646757{col 71}{space 3} .2956239
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.1497927{col 30}{space 2} .1033057{col 41}{space 1}   -1.45{col 50}{space 3}0.147{col 58}{space 4}-.3522682{col 71}{space 3} .0526827
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .1162588{col 30}{space 2} .0379473{col 41}{space 1}    3.06{col 50}{space 3}0.002{col 58}{space 4} .0418835{col 71}{space 3} .1906341
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5621488{col 30}{space 2} .0625814{col 41}{space 1}   -8.98{col 50}{space 3}0.000{col 58}{space 4}-.6848061{col 71}{space 3}-.4394915
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} -.497314{col 30}{space 2} .0595537{col 41}{space 1}   -8.35{col 50}{space 3}0.000{col 58}{space 4}-.6140372{col 71}{space 3}-.3805908
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3969887{col 30}{space 2} .0584201{col 41}{space 1}   -6.80{col 50}{space 3}0.000{col 58}{space 4}-.5114899{col 71}{space 3}-.2824874
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.549408{col 30}{space 2} .2283312{col 41}{space 1}   19.92{col 50}{space 3}0.000{col 58}{space 4} 4.101887{col 71}{space 3} 4.996929
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .67070053
         {txt}sigma_e {c |} {res}  1.238356
             {txt}rho {c |} {res} .22680607{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     1,113
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}       271

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0335                                         {txt}min = {res}         1
{txt}     between = {res}0.3649                                         {txt}avg = {res}       4.1
{txt}     overall = {res}0.2495                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}   245.40
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:271} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0676486{col 30}{space 2} .0480734{col 41}{space 1}    1.41{col 50}{space 3}0.159{col 58}{space 4}-.0265735{col 71}{space 3} .1618706
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0228966{col 30}{space 2} .0194493{col 41}{space 1}   -1.18{col 50}{space 3}0.239{col 58}{space 4}-.0610164{col 71}{space 3} .0152233
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0472128{col 30}{space 2} .0206895{col 41}{space 1}   -2.28{col 50}{space 3}0.022{col 58}{space 4}-.0877634{col 71}{space 3}-.0066621
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .4017117{col 30}{space 2} .2210402{col 41}{space 1}    1.82{col 50}{space 3}0.069{col 58}{space 4}-.0315191{col 71}{space 3} .8349425
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0058047{col 30}{space 2} .0040121{col 41}{space 1}   -1.45{col 50}{space 3}0.148{col 58}{space 4}-.0136682{col 71}{space 3} .0020588
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3332902{col 30}{space 2} .1305154{col 41}{space 1}    2.55{col 50}{space 3}0.011{col 58}{space 4} .0774848{col 71}{space 3} .5890957
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1972146{col 30}{space 2} .1261429{col 41}{space 1}    1.56{col 50}{space 3}0.118{col 58}{space 4} -.050021{col 71}{space 3} .4444502
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2253721{col 30}{space 2} .1867891{col 41}{space 1}    1.21{col 50}{space 3}0.228{col 58}{space 4}-.1407278{col 71}{space 3} .5914719
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2750456{col 30}{space 2}  .120692{col 41}{space 1}    2.28{col 50}{space 3}0.023{col 58}{space 4} .0384935{col 71}{space 3} .5115976
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0854701{col 30}{space 2} .1254339{col 41}{space 1}   -0.68{col 50}{space 3}0.496{col 58}{space 4}-.3313161{col 71}{space 3} .1603759
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0897417{col 30}{space 2} .0948787{col 41}{space 1}    0.95{col 50}{space 3}0.344{col 58}{space 4}-.0962172{col 71}{space 3} .2757006
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2756279{col 30}{space 2} .1048549{col 41}{space 1}    2.63{col 50}{space 3}0.009{col 58}{space 4}  .070116{col 71}{space 3} .4811398
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1759233{col 30}{space 2} .1106892{col 41}{space 1}   -1.59{col 50}{space 3}0.112{col 58}{space 4}-.3928702{col 71}{space 3} .0410236
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0133851{col 30}{space 2} .0134136{col 41}{space 1}    1.00{col 50}{space 3}0.318{col 58}{space 4} -.012905{col 71}{space 3} .0396752
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0849886{col 30}{space 2} .0971319{col 41}{space 1}    0.87{col 50}{space 3}0.382{col 58}{space 4}-.1053863{col 71}{space 3} .2753636
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .7982392{col 30}{space 2} .3614643{col 41}{space 1}    2.21{col 50}{space 3}0.027{col 58}{space 4} .0897822{col 71}{space 3} 1.506696
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7117322{col 30}{space 2} .2436936{col 41}{space 1}    2.92{col 50}{space 3}0.003{col 58}{space 4} .2341015{col 71}{space 3} 1.189363
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.101188{col 30}{space 2} .2521171{col 41}{space 1}    4.37{col 50}{space 3}0.000{col 58}{space 4} .6070472{col 71}{space 3} 1.595328
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2065756{col 30}{space 2} .2136367{col 41}{space 1}   -0.97{col 50}{space 3}0.334{col 58}{space 4}-.6252958{col 71}{space 3} .2121445
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0910537{col 30}{space 2} .2233616{col 41}{space 1}    0.41{col 50}{space 3}0.684{col 58}{space 4}-.3467271{col 71}{space 3} .5288345
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} -.024564{col 30}{space 2} .0722238{col 41}{space 1}   -0.34{col 50}{space 3}0.734{col 58}{space 4}-.1661201{col 71}{space 3}  .116992
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.0477336{col 30}{space 2} .1082671{col 41}{space 1}   -0.44{col 50}{space 3}0.659{col 58}{space 4}-.2599333{col 71}{space 3}  .164466
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0704807{col 30}{space 2}  .090964{col 41}{space 1}   -0.77{col 50}{space 3}0.438{col 58}{space 4}-.2487669{col 71}{space 3} .1078054
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .1040722{col 30}{space 2} .1013149{col 41}{space 1}    1.03{col 50}{space 3}0.304{col 58}{space 4}-.0945015{col 71}{space 3} .3026458
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.702863{col 30}{space 2} .4432988{col 41}{space 1}   10.61{col 50}{space 3}0.000{col 58}{space 4} 3.834013{col 71}{space 3} 5.571713
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .78982767
         {txt}sigma_e {c |} {res} 1.1563623
             {txt}rho {c |} {res} .31811692{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     6,588
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,089

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0646                                         {txt}min = {res}         1
{txt}     between = {res}0.3124                                         {txt}avg = {res}       6.0
{txt}     overall = {res}0.1805                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}   911.64
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,089} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0284881{col 30}{space 2}  .019207{col 41}{space 1}    1.48{col 50}{space 3}0.138{col 58}{space 4}-.0091569{col 71}{space 3}  .066133
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0199901{col 30}{space 2} .0067597{col 41}{space 1}   -2.96{col 50}{space 3}0.003{col 58}{space 4}-.0332389{col 71}{space 3}-.0067413
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0042505{col 30}{space 2} .0085909{col 41}{space 1}    0.49{col 50}{space 3}0.621{col 58}{space 4}-.0125874{col 71}{space 3} .0210885
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}   .09915{col 30}{space 2} .0924732{col 41}{space 1}    1.07{col 50}{space 3}0.284{col 58}{space 4}-.0820942{col 71}{space 3} .2803943
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0003427{col 30}{space 2} .0018572{col 41}{space 1}    0.18{col 50}{space 3}0.854{col 58}{space 4}-.0032975{col 71}{space 3} .0039828
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0035131{col 30}{space 2} .0564569{col 41}{space 1}   -0.06{col 50}{space 3}0.950{col 58}{space 4}-.1141666{col 71}{space 3} .1071403
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2816395{col 30}{space 2} .0520185{col 41}{space 1}    5.41{col 50}{space 3}0.000{col 58}{space 4} .1796851{col 71}{space 3} .3835939
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1891656{col 30}{space 2} .0750417{col 41}{space 1}    2.52{col 50}{space 3}0.012{col 58}{space 4} .0420865{col 71}{space 3} .3362446
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .304031{col 30}{space 2}  .051702{col 41}{space 1}    5.88{col 50}{space 3}0.000{col 58}{space 4} .2026969{col 71}{space 3} .4053651
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3606181{col 30}{space 2} .0523444{col 41}{space 1}    6.89{col 50}{space 3}0.000{col 58}{space 4} .2580249{col 71}{space 3} .4632113
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0389807{col 30}{space 2} .0423549{col 41}{space 1}    0.92{col 50}{space 3}0.357{col 58}{space 4}-.0440332{col 71}{space 3} .1219947
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1869693{col 30}{space 2} .0446318{col 41}{space 1}    4.19{col 50}{space 3}0.000{col 58}{space 4} .0994927{col 71}{space 3}  .274446
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0117583{col 30}{space 2} .0362621{col 41}{space 1}    0.32{col 50}{space 3}0.746{col 58}{space 4}-.0593141{col 71}{space 3} .0828307
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0017419{col 30}{space 2} .0017798{col 41}{space 1}    0.98{col 50}{space 3}0.328{col 58}{space 4}-.0017464{col 71}{space 3} .0052302
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0129808{col 30}{space 2} .0418987{col 41}{space 1}   -0.31{col 50}{space 3}0.757{col 58}{space 4}-.0951008{col 71}{space 3} .0691392
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1509486{col 30}{space 2} .1402365{col 41}{space 1}    1.08{col 50}{space 3}0.282{col 58}{space 4}-.1239098{col 71}{space 3} .4258071
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .2719612{col 30}{space 2} .1080115{col 41}{space 1}    2.52{col 50}{space 3}0.012{col 58}{space 4} .0602624{col 71}{space 3} .4836599
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4549919{col 30}{space 2} .1333976{col 41}{space 1}    3.41{col 50}{space 3}0.001{col 58}{space 4} .1935375{col 71}{space 3} .7164463
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .078948{col 30}{space 2} .0994128{col 41}{space 1}    0.79{col 50}{space 3}0.427{col 58}{space 4}-.1158975{col 71}{space 3} .2737934
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2914185{col 30}{space 2} .0910449{col 41}{space 1}    3.20{col 50}{space 3}0.001{col 58}{space 4} .1129738{col 71}{space 3} .4698633
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .1450139{col 30}{space 2} .0367345{col 41}{space 1}    3.95{col 50}{space 3}0.000{col 58}{space 4} .0730157{col 71}{space 3} .2170122
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1269393{col 30}{space 2}  .057564{col 41}{space 1}   -2.21{col 50}{space 3}0.027{col 58}{space 4}-.2397627{col 71}{space 3} -.014116
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.1263222{col 30}{space 2} .0503653{col 41}{space 1}   -2.51{col 50}{space 3}0.012{col 58}{space 4}-.2250364{col 71}{space 3} -.027608
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3594901{col 30}{space 2} .0497777{col 41}{space 1}    7.22{col 50}{space 3}0.000{col 58}{space 4} .2619276{col 71}{space 3} .4570525
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1413455{col 30}{space 2} .0498299{col 41}{space 1}    2.84{col 50}{space 3}0.005{col 58}{space 4} .0436807{col 71}{space 3} .2390103
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .3399628{col 30}{space 2} .0483606{col 41}{space 1}    7.03{col 50}{space 3}0.000{col 58}{space 4} .2451777{col 71}{space 3} .4347478
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.509231{col 30}{space 2} .2387406{col 41}{space 1}   14.70{col 50}{space 3}0.000{col 58}{space 4} 3.041308{col 71}{space 3} 3.977154
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69753654
         {txt}sigma_e {c |} {res} 1.2267601
             {txt}rho {c |} {res} .24431727{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S16_balance.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9_vill    $xlist  pdd9_mean_vill sum_vill _cons)
{res}{txt}(note: file S16_balance.rtf not found)
(output written to {browse  `"S16_balance.rtf"'})

{com}. 
. 
. 
. 
. 
. 
. *                          town_village_level                                  *
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town i.country i.year   , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    30,867
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     9,851

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0333                                         {txt}min = {res}         1
{txt}     between = {res}0.4829                                         {txt}avg = {res}       3.1
{txt}     overall = {res}0.3287                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 11124.73
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:9,851} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0341442{col 30}{space 2} .0097765{col 41}{space 1}    3.49{col 50}{space 3}0.000{col 58}{space 4} .0149825{col 71}{space 3} .0533058
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0020142{col 30}{space 2} .0002472{col 41}{space 1}   -8.15{col 50}{space 3}0.000{col 58}{space 4}-.0024986{col 71}{space 3}-.0015297
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0096369{col 30}{space 2} .0037188{col 41}{space 1}    2.59{col 50}{space 3}0.010{col 58}{space 4} .0023481{col 71}{space 3} .0169256
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0438417{col 30}{space 2} .0408642{col 41}{space 1}   -1.07{col 50}{space 3}0.283{col 58}{space 4} -.123934{col 71}{space 3} .0362507
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0004936{col 30}{space 2} .0007041{col 41}{space 1}   -0.70{col 50}{space 3}0.483{col 58}{space 4}-.0018736{col 71}{space 3} .0008864
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0248323{col 30}{space 2} .0251902{col 41}{space 1}   -0.99{col 50}{space 3}0.324{col 58}{space 4}-.0742042{col 71}{space 3} .0245395
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2687573{col 30}{space 2} .0209494{col 41}{space 1}   12.83{col 50}{space 3}0.000{col 58}{space 4} .2276973{col 71}{space 3} .3098173
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1386356{col 30}{space 2} .0431282{col 41}{space 1}    3.21{col 50}{space 3}0.001{col 58}{space 4} .0541058{col 71}{space 3} .2231653
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1616081{col 30}{space 2} .0254408{col 41}{space 1}    6.35{col 50}{space 3}0.000{col 58}{space 4}  .111745{col 71}{space 3} .2114712
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1414485{col 30}{space 2} .0310277{col 41}{space 1}    4.56{col 50}{space 3}0.000{col 58}{space 4} .0806355{col 71}{space 3} .2022616
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1138708{col 30}{space 2} .0288667{col 41}{space 1}    3.94{col 50}{space 3}0.000{col 58}{space 4}  .057293{col 71}{space 3} .1704486
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1643972{col 30}{space 2} .0246309{col 41}{space 1}    6.67{col 50}{space 3}0.000{col 58}{space 4} .1161214{col 71}{space 3} .2126729
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0897484{col 30}{space 2} .0191947{col 41}{space 1}   -4.68{col 50}{space 3}0.000{col 58}{space 4}-.1273694{col 71}{space 3}-.0521274
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0007829{col 30}{space 2} .0013504{col 41}{space 1}    0.58{col 50}{space 3}0.562{col 58}{space 4}-.0018638{col 71}{space 3} .0034296
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1353989{col 30}{space 2} .0225004{col 41}{space 1}    6.02{col 50}{space 3}0.000{col 58}{space 4}  .091299{col 71}{space 3} .1794989
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0352226{col 30}{space 2} .0639663{col 41}{space 1}    0.55{col 50}{space 3}0.582{col 58}{space 4} -.090149{col 71}{space 3} .1605942
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5295747{col 30}{space 2}  .040788{col 41}{space 1}   12.98{col 50}{space 3}0.000{col 58}{space 4} .4496317{col 71}{space 3} .6095178
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6612633{col 30}{space 2} .0470671{col 41}{space 1}   14.05{col 50}{space 3}0.000{col 58}{space 4} .5690135{col 71}{space 3}  .753513
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3284699{col 30}{space 2} .0489068{col 41}{space 1}    6.72{col 50}{space 3}0.000{col 58}{space 4} .2326143{col 71}{space 3} .4243254
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1975894{col 30}{space 2} .0376697{col 41}{space 1}    5.25{col 50}{space 3}0.000{col 58}{space 4} .1237581{col 71}{space 3} .2714207
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0998381{col 30}{space 2} .0137582{col 41}{space 1}    7.26{col 50}{space 3}0.000{col 58}{space 4} .0728726{col 71}{space 3} .1268037
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.4243099{col 30}{space 2} .0522871{col 41}{space 1}   -8.12{col 50}{space 3}0.000{col 58}{space 4}-.5267907{col 71}{space 3}-.3218292
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.606857{col 30}{space 2} .0431656{col 41}{space 1}  -37.23{col 50}{space 3}0.000{col 58}{space 4} -1.69146{col 71}{space 3}-1.522254
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.5810709{col 30}{space 2} .0470986{col 41}{space 1}  -12.34{col 50}{space 3}0.000{col 58}{space 4}-.6733825{col 71}{space 3}-.4887594
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.3730226{col 30}{space 2} .0729273{col 41}{space 1}   -5.11{col 50}{space 3}0.000{col 58}{space 4}-.5159574{col 71}{space 3}-.2300878
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .2824796{col 30}{space 2}  .052425{col 41}{space 1}    5.39{col 50}{space 3}0.000{col 58}{space 4} .1797284{col 71}{space 3} .3852308
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.1946107{col 30}{space 2} .1002797{col 41}{space 1}   -1.94{col 50}{space 3}0.052{col 58}{space 4}-.3911553{col 71}{space 3} .0019339
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0267234{col 30}{space 2} .0912942{col 41}{space 1}    0.29{col 50}{space 3}0.770{col 58}{space 4}  -.15221{col 71}{space 3} .2056567
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0435253{col 30}{space 2} .0921186{col 41}{space 1}    0.47{col 50}{space 3}0.637{col 58}{space 4} -.137024{col 71}{space 3} .2240745
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0685694{col 30}{space 2} .0944235{col 41}{space 1}    0.73{col 50}{space 3}0.468{col 58}{space 4}-.1164972{col 71}{space 3} .2536361
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0825661{col 30}{space 2} .0925334{col 41}{space 1}    0.89{col 50}{space 3}0.372{col 58}{space 4} -.098796{col 71}{space 3} .2639282
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.1752115{col 30}{space 2} .0949618{col 41}{space 1}   -1.85{col 50}{space 3}0.065{col 58}{space 4}-.3613331{col 71}{space 3} .0109102
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .2448114{col 30}{space 2} .0928638{col 41}{space 1}    2.64{col 50}{space 3}0.008{col 58}{space 4} .0628016{col 71}{space 3} .4268211
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.1761685{col 30}{space 2}  .102784{col 41}{space 1}   -1.71{col 50}{space 3}0.087{col 58}{space 4}-.3776214{col 71}{space 3} .0252845
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .5249098{col 30}{space 2} .0956681{col 41}{space 1}    5.49{col 50}{space 3}0.000{col 58}{space 4} .3374038{col 71}{space 3} .7124158
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}  .140595{col 30}{space 2} .0940841{col 41}{space 1}    1.49{col 50}{space 3}0.135{col 58}{space 4}-.0438064{col 71}{space 3} .3249964
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.079119{col 30}{space 2} .1186016{col 41}{space 1}   34.39{col 50}{space 3}0.000{col 58}{space 4} 3.846664{col 71}{space 3} 4.311574
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .71141392
         {txt}sigma_e {c |} {res} 1.2195326
             {txt}rho {c |} {res} .25389662{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,299
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,149

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0241                                         {txt}min = {res}         1
{txt}     between = {res}0.3159                                         {txt}avg = {res}       3.0
{txt}     overall = {res}0.2004                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1671.12
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,149} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0627566{col 30}{space 2} .0167839{col 41}{space 1}    3.74{col 50}{space 3}0.000{col 58}{space 4} .0298608{col 71}{space 3} .0956523
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0058679{col 30}{space 2} .0006454{col 41}{space 1}   -9.09{col 50}{space 3}0.000{col 58}{space 4}-.0071328{col 71}{space 3} -.004603
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0515687{col 30}{space 2}  .007713{col 41}{space 1}    6.69{col 50}{space 3}0.000{col 58}{space 4} .0364516{col 71}{space 3} .0666859
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0521127{col 30}{space 2} .0650149{col 41}{space 1}   -0.80{col 50}{space 3}0.423{col 58}{space 4}-.1795396{col 71}{space 3} .0753141
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0026741{col 30}{space 2} .0010981{col 41}{space 1}   -2.44{col 50}{space 3}0.015{col 58}{space 4}-.0048264{col 71}{space 3}-.0005219
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0358924{col 30}{space 2}  .040791{col 41}{space 1}   -0.88{col 50}{space 3}0.379{col 58}{space 4}-.1158414{col 71}{space 3} .0440565
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2939865{col 30}{space 2} .0334278{col 41}{space 1}    8.79{col 50}{space 3}0.000{col 58}{space 4} .2284693{col 71}{space 3} .3595038
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} -.244286{col 30}{space 2} .1591783{col 41}{space 1}   -1.53{col 50}{space 3}0.125{col 58}{space 4}-.5562698{col 71}{space 3} .0676978
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .194338{col 30}{space 2} .0388407{col 41}{space 1}    5.00{col 50}{space 3}0.000{col 58}{space 4} .1182117{col 71}{space 3} .2704644
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1299417{col 30}{space 2} .0481666{col 41}{space 1}    2.70{col 50}{space 3}0.007{col 58}{space 4} .0355369{col 71}{space 3} .2243465
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .068425{col 30}{space 2} .0722985{col 41}{space 1}    0.95{col 50}{space 3}0.344{col 58}{space 4}-.0732775{col 71}{space 3} .2101275
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1901719{col 30}{space 2} .0522742{col 41}{space 1}    3.64{col 50}{space 3}0.000{col 58}{space 4} .0877163{col 71}{space 3} .2926275
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1102702{col 30}{space 2} .0314288{col 41}{space 1}   -3.51{col 50}{space 3}0.000{col 58}{space 4}-.1718694{col 71}{space 3}-.0486709
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0139318{col 30}{space 2} .0039338{col 41}{space 1}    3.54{col 50}{space 3}0.000{col 58}{space 4} .0062216{col 71}{space 3}  .021642
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2144726{col 30}{space 2} .0327539{col 41}{space 1}    6.55{col 50}{space 3}0.000{col 58}{space 4} .1502761{col 71}{space 3}  .278669
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} 1.013443{col 30}{space 2} .2970038{col 41}{space 1}    3.41{col 50}{space 3}0.001{col 58}{space 4} .4313264{col 71}{space 3}  1.59556
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3882292{col 30}{space 2} .0616987{col 41}{space 1}    6.29{col 50}{space 3}0.000{col 58}{space 4} .2673019{col 71}{space 3} .5091566
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4256355{col 30}{space 2}  .075725{col 41}{space 1}    5.62{col 50}{space 3}0.000{col 58}{space 4} .2772173{col 71}{space 3} .5740538
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .5007038{col 30}{space 2} .1336713{col 41}{space 1}    3.75{col 50}{space 3}0.000{col 58}{space 4} .2387129{col 71}{space 3} .7626948
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1481208{col 30}{space 2} .0689548{col 41}{space 1}    2.15{col 50}{space 3}0.032{col 58}{space 4}  .012972{col 71}{space 3} .2832696
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .1207074{col 30}{space 2} .0217794{col 41}{space 1}    5.54{col 50}{space 3}0.000{col 58}{space 4} .0780205{col 71}{space 3} .1633942
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1854431{col 30}{space 2} .0235802{col 41}{space 1}   -7.86{col 50}{space 3}0.000{col 58}{space 4}-.2316594{col 71}{space 3}-.1392267
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.322492{col 30}{space 2} .1155144{col 41}{space 1}   20.11{col 50}{space 3}0.000{col 58}{space 4} 2.096088{col 71}{space 3} 2.548896
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .65935448
         {txt}sigma_e {c |} {res} 1.0651077
             {txt}rho {c |} {res} .27705047{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_MALAWI  if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,301
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,381

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0212                                         {txt}min = {res}         1
{txt}     between = {res}0.4049                                         {txt}avg = {res}       3.1
{txt}     overall = {res}0.2736                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1401.07
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,381} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2}  .037955{col 30}{space 2} .0274296{col 41}{space 1}    1.38{col 50}{space 3}0.166{col 58}{space 4} -.015806{col 71}{space 3} .0917161
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0135809{col 30}{space 2} .0036349{col 41}{space 1}   -3.74{col 50}{space 3}0.000{col 58}{space 4}-.0207053{col 71}{space 3}-.0064566
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}  .003395{col 30}{space 2} .0115731{col 41}{space 1}    0.29{col 50}{space 3}0.769{col 58}{space 4}-.0192878{col 71}{space 3} .0260777
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2735208{col 30}{space 2} .1069959{col 41}{space 1}   -2.56{col 50}{space 3}0.011{col 58}{space 4}-.4832289{col 71}{space 3}-.0638126
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0008156{col 30}{space 2} .0018086{col 41}{space 1}   -0.45{col 50}{space 3}0.652{col 58}{space 4}-.0043604{col 71}{space 3} .0027293
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0922094{col 30}{space 2} .0627894{col 41}{space 1}   -1.47{col 50}{space 3}0.142{col 58}{space 4}-.2152744{col 71}{space 3} .0308556
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3135143{col 30}{space 2} .0604334{col 41}{space 1}    5.19{col 50}{space 3}0.000{col 58}{space 4} .1950671{col 71}{space 3} .4319616
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2164908{col 30}{space 2} .1980454{col 41}{space 1}    1.09{col 50}{space 3}0.274{col 58}{space 4}-.1716711{col 71}{space 3} .6046527
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0798365{col 30}{space 2} .0712698{col 41}{space 1}    1.12{col 50}{space 3}0.263{col 58}{space 4}-.0598497{col 71}{space 3} .2195228
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .129689{col 30}{space 2} .1432998{col 41}{space 1}    0.91{col 50}{space 3}0.365{col 58}{space 4}-.1511735{col 71}{space 3} .4105515
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1316955{col 30}{space 2} .0832176{col 41}{space 1}    1.58{col 50}{space 3}0.114{col 58}{space 4}-.0314079{col 71}{space 3} .2947989
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2334653{col 30}{space 2}  .057648{col 41}{space 1}    4.05{col 50}{space 3}0.000{col 58}{space 4} .1204774{col 71}{space 3} .3464533
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1641383{col 30}{space 2}  .044931{col 41}{space 1}   -3.65{col 50}{space 3}0.000{col 58}{space 4}-.2522014{col 71}{space 3}-.0760752
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0947949{col 30}{space 2}  .038774{col 41}{space 1}    2.44{col 50}{space 3}0.014{col 58}{space 4} .0187992{col 71}{space 3} .1707906
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0876943{col 30}{space 2} .0635599{col 41}{space 1}    1.38{col 50}{space 3}0.168{col 58}{space 4}-.0368809{col 71}{space 3} .2122695
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0415839{col 30}{space 2} .3330579{col 41}{space 1}    0.12{col 50}{space 3}0.901{col 58}{space 4}-.6111977{col 71}{space 3} .6943654
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7420599{col 30}{space 2} .1135565{col 41}{space 1}    6.53{col 50}{space 3}0.000{col 58}{space 4} .5194933{col 71}{space 3} .9646266
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .889434{col 30}{space 2} .1843695{col 41}{space 1}    4.82{col 50}{space 3}0.000{col 58}{space 4} .5280764{col 71}{space 3} 1.250792
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3976209{col 30}{space 2} .1192258{col 41}{space 1}    3.34{col 50}{space 3}0.001{col 58}{space 4} .1639426{col 71}{space 3} .6312992
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2965313{col 30}{space 2} .1052805{col 41}{space 1}    2.82{col 50}{space 3}0.005{col 58}{space 4} .0901854{col 71}{space 3} .5028773
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2}-.0315322{col 30}{space 2} .0408899{col 41}{space 1}   -0.77{col 50}{space 3}0.441{col 58}{space 4} -.111675{col 71}{space 3} .0486106
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .2506879{col 30}{space 2} .0578935{col 41}{space 1}    4.33{col 50}{space 3}0.000{col 58}{space 4} .1372189{col 71}{space 3}  .364157
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .1135713{col 30}{space 2}  .051192{col 41}{space 1}    2.22{col 50}{space 3}0.027{col 58}{space 4} .0132367{col 71}{space 3} .2139059
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.176887{col 30}{space 2} .2353286{col 41}{space 1}   22.00{col 50}{space 3}0.000{col 58}{space 4} 4.715651{col 71}{space 3} 5.638122
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69219175
         {txt}sigma_e {c |} {res} 1.2919187
             {txt}rho {c |} {res} .22303934{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9 pdd9_town sum_town  $xlist  pdd9_mean_town $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,552
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,853

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0276                                         {txt}min = {res}         1
{txt}     between = {res}0.2665                                         {txt}avg = {res}       1.9
{txt}     overall = {res}0.1786                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1175.73
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,853} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0789032{col 30}{space 2} .0300704{col 41}{space 1}    2.62{col 50}{space 3}0.009{col 58}{space 4} .0199662{col 71}{space 3} .1378402
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0016098{col 30}{space 2} .0003595{col 41}{space 1}   -4.48{col 50}{space 3}0.000{col 58}{space 4}-.0023144{col 71}{space 3}-.0009052
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0077345{col 30}{space 2} .0069081{col 41}{space 1}    1.12{col 50}{space 3}0.263{col 58}{space 4}-.0058052{col 71}{space 3} .0212743
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1065254{col 30}{space 2} .1109131{col 41}{space 1}   -0.96{col 50}{space 3}0.337{col 58}{space 4} -.323911{col 71}{space 3} .1108602
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0028768{col 30}{space 2} .0015668{col 41}{space 1}    1.84{col 50}{space 3}0.066{col 58}{space 4}-.0001941{col 71}{space 3} .0059477
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0852406{col 30}{space 2} .0635333{col 41}{space 1}    1.34{col 50}{space 3}0.180{col 58}{space 4}-.0392823{col 71}{space 3} .2097636
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2989766{col 30}{space 2} .0500486{col 41}{space 1}    5.97{col 50}{space 3}0.000{col 58}{space 4} .2008832{col 71}{space 3} .3970699
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .343142{col 30}{space 2} .1115768{col 41}{space 1}    3.08{col 50}{space 3}0.002{col 58}{space 4} .1244556{col 71}{space 3} .5618285
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1291497{col 30}{space 2} .0789487{col 41}{space 1}    1.64{col 50}{space 3}0.102{col 58}{space 4} -.025587{col 71}{space 3} .2838864
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2753686{col 30}{space 2} .1252427{col 41}{space 1}    2.20{col 50}{space 3}0.028{col 58}{space 4} .0298973{col 71}{space 3} .5208398
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2033682{col 30}{space 2} .0908968{col 41}{space 1}    2.24{col 50}{space 3}0.025{col 58}{space 4} .0252137{col 71}{space 3} .3815227
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} -.162471{col 30}{space 2}  .069825{col 41}{space 1}   -2.33{col 50}{space 3}0.020{col 58}{space 4}-.2993255{col 71}{space 3}-.0256164
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1363631{col 30}{space 2} .0481814{col 41}{space 1}   -2.83{col 50}{space 3}0.005{col 58}{space 4}-.2307969{col 71}{space 3}-.0419293
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0012973{col 30}{space 2} .0017444{col 41}{space 1}   -0.74{col 50}{space 3}0.457{col 58}{space 4}-.0047163{col 71}{space 3} .0021217
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1438703{col 30}{space 2} .2370202{col 41}{space 1}    0.61{col 50}{space 3}0.544{col 58}{space 4}-.3206807{col 71}{space 3} .6084212
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0466946{col 30}{space 2} .1405019{col 41}{space 1}    0.33{col 50}{space 3}0.740{col 58}{space 4} -.228684{col 71}{space 3} .3220732
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3427476{col 30}{space 2} .1018559{col 41}{space 1}    3.37{col 50}{space 3}0.001{col 58}{space 4} .1431137{col 71}{space 3} .5423814
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4982763{col 30}{space 2} .1453606{col 41}{space 1}    3.43{col 50}{space 3}0.001{col 58}{space 4} .2133747{col 71}{space 3} .7831778
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1988564{col 30}{space 2}  .117708{col 41}{space 1}    1.69{col 50}{space 3}0.091{col 58}{space 4} -.031847{col 71}{space 3} .4295598
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4616547{col 30}{space 2} .0897966{col 41}{space 1}    5.14{col 50}{space 3}0.000{col 58}{space 4} .2856567{col 71}{space 3} .6376528
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0670614{col 30}{space 2} .0384847{col 41}{space 1}    1.74{col 50}{space 3}0.081{col 58}{space 4}-.0083673{col 71}{space 3}   .14249
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2743872{col 30}{space 2} .0417068{col 41}{space 1}    6.58{col 50}{space 3}0.000{col 58}{space 4} .1926434{col 71}{space 3} .3561309
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.811306{col 30}{space 2} .1659037{col 41}{space 1}   22.97{col 50}{space 3}0.000{col 58}{space 4} 3.486141{col 71}{space 3} 4.136471
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .54489345
         {txt}sigma_e {c |} {res} 1.3965162
             {txt}rho {c |} {res}  .1321259{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,014
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,108

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0662                                         {txt}min = {res}         1
{txt}     between = {res}0.4101                                         {txt}avg = {res}       3.6
{txt}     overall = {res}0.2545                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}   943.37
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,108} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0888061{col 30}{space 2} .0249105{col 41}{space 1}    3.56{col 50}{space 3}0.000{col 58}{space 4} .0399823{col 71}{space 3} .1376298
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0249424{col 30}{space 2} .0051418{col 41}{space 1}   -4.85{col 50}{space 3}0.000{col 58}{space 4}-.0350201{col 71}{space 3}-.0148647
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0007238{col 30}{space 2} .0084068{col 41}{space 1}   -0.09{col 50}{space 3}0.931{col 58}{space 4}-.0172008{col 71}{space 3} .0157532
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0009708{col 30}{space 2} .1056938{col 41}{space 1}   -0.01{col 50}{space 3}0.993{col 58}{space 4}-.2081269{col 71}{space 3} .2061852
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0048976{col 30}{space 2} .0019676{col 41}{space 1}    2.49{col 50}{space 3}0.013{col 58}{space 4} .0010412{col 71}{space 3}  .008754
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1303926{col 30}{space 2} .0752171{col 41}{space 1}    1.73{col 50}{space 3}0.083{col 58}{space 4}-.0170302{col 71}{space 3} .2778155
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0555823{col 30}{space 2} .0509993{col 41}{space 1}    1.09{col 50}{space 3}0.276{col 58}{space 4}-.0443746{col 71}{space 3} .1555391
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0451516{col 30}{space 2} .0696744{col 41}{space 1}    0.65{col 50}{space 3}0.517{col 58}{space 4}-.0914077{col 71}{space 3} .1817108
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1871865{col 30}{space 2} .0677253{col 41}{space 1}    2.76{col 50}{space 3}0.006{col 58}{space 4} .0544473{col 71}{space 3} .3199257
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1116121{col 30}{space 2} .0874862{col 41}{space 1}    1.28{col 50}{space 3}0.202{col 58}{space 4}-.0598577{col 71}{space 3} .2830818
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2669859{col 30}{space 2} .0943524{col 41}{space 1}    2.83{col 50}{space 3}0.005{col 58}{space 4} .0820587{col 71}{space 3} .4519132
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3057775{col 30}{space 2}  .066979{col 41}{space 1}    4.57{col 50}{space 3}0.000{col 58}{space 4}  .174501{col 71}{space 3}  .437054
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0319175{col 30}{space 2} .0898227{col 41}{space 1}    0.36{col 50}{space 3}0.722{col 58}{space 4}-.1441316{col 71}{space 3} .2079667
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0018822{col 30}{space 2} .0129634{col 41}{space 1}    0.15{col 50}{space 3}0.885{col 58}{space 4}-.0235255{col 71}{space 3}   .02729
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1669618{col 30}{space 2} .1187902{col 41}{space 1}    1.41{col 50}{space 3}0.160{col 58}{space 4}-.0658626{col 71}{space 3} .3997862
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0564513{col 30}{space 2} .1120688{col 41}{space 1}   -0.50{col 50}{space 3}0.614{col 58}{space 4}-.2761021{col 71}{space 3} .1631994
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .9258365{col 30}{space 2} .1285005{col 41}{space 1}    7.20{col 50}{space 3}0.000{col 58}{space 4} .6739802{col 71}{space 3} 1.177693
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8166358{col 30}{space 2} .1192936{col 41}{space 1}    6.85{col 50}{space 3}0.000{col 58}{space 4} .5828247{col 71}{space 3} 1.050447
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .086813{col 30}{space 2} .1432855{col 41}{space 1}    0.61{col 50}{space 3}0.545{col 58}{space 4}-.1940215{col 71}{space 3} .3676475
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0879915{col 30}{space 2} .1037075{col 41}{space 1}   -0.85{col 50}{space 3}0.396{col 58}{space 4}-.2912545{col 71}{space 3} .1152716
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0798009{col 30}{space 2} .0385788{col 41}{space 1}    2.07{col 50}{space 3}0.039{col 58}{space 4} .0041879{col 71}{space 3} .1554139
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.6227264{col 30}{space 2}  .063952{col 41}{space 1}   -9.74{col 50}{space 3}0.000{col 58}{space 4}-.7480701{col 71}{space 3}-.4973828
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} -.523007{col 30}{space 2} .0605907{col 41}{space 1}   -8.63{col 50}{space 3}0.000{col 58}{space 4}-.6417626{col 71}{space 3}-.4042514
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.4112999{col 30}{space 2} .0591439{col 41}{space 1}   -6.95{col 50}{space 3}0.000{col 58}{space 4}-.5272198{col 71}{space 3}-.2953801
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.002722{col 30}{space 2} .2080206{col 41}{space 1}   19.24{col 50}{space 3}0.000{col 58}{space 4} 3.595009{col 71}{space 3} 4.410434
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .67741277
         {txt}sigma_e {c |} {res} 1.2396385
             {txt}rho {c |} {res} .22995088{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     1,113
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}       271

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0310                                         {txt}min = {res}         1
{txt}     between = {res}0.3678                                         {txt}avg = {res}       4.1
{txt}     overall = {res}0.2491                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}   235.44
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:271} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0212243{col 30}{space 2} .0477354{col 41}{space 1}    0.44{col 50}{space 3}0.657{col 58}{space 4}-.0723353{col 71}{space 3}  .114784
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0118951{col 30}{space 2} .0148557{col 41}{space 1}   -0.80{col 50}{space 3}0.423{col 58}{space 4}-.0410117{col 71}{space 3} .0172216
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0470201{col 30}{space 2} .0207865{col 41}{space 1}   -2.26{col 50}{space 3}0.024{col 58}{space 4}-.0877609{col 71}{space 3}-.0062794
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .419104{col 30}{space 2} .2193531{col 41}{space 1}    1.91{col 50}{space 3}0.056{col 58}{space 4}-.0108202{col 71}{space 3} .8490282
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0057907{col 30}{space 2} .0039533{col 41}{space 1}   -1.46{col 50}{space 3}0.143{col 58}{space 4} -.013539{col 71}{space 3} .0019576
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3333331{col 30}{space 2} .1285638{col 41}{space 1}    2.59{col 50}{space 3}0.010{col 58}{space 4} .0813527{col 71}{space 3} .5853135
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2021164{col 30}{space 2} .1239277{col 41}{space 1}    1.63{col 50}{space 3}0.103{col 58}{space 4}-.0407774{col 71}{space 3} .4450103
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2064726{col 30}{space 2} .1883078{col 41}{space 1}    1.10{col 50}{space 3}0.273{col 58}{space 4}-.1626039{col 71}{space 3} .5755491
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2747614{col 30}{space 2} .1199014{col 41}{space 1}    2.29{col 50}{space 3}0.022{col 58}{space 4} .0397589{col 71}{space 3} .5097639
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0919308{col 30}{space 2} .1265843{col 41}{space 1}   -0.73{col 50}{space 3}0.468{col 58}{space 4}-.3400313{col 71}{space 3} .1561698
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0958367{col 30}{space 2} .0950735{col 41}{space 1}    1.01{col 50}{space 3}0.313{col 58}{space 4}-.0905039{col 71}{space 3} .2821772
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2803611{col 30}{space 2} .1056206{col 41}{space 1}    2.65{col 50}{space 3}0.008{col 58}{space 4} .0733486{col 71}{space 3} .4873736
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1716758{col 30}{space 2} .1110293{col 41}{space 1}   -1.55{col 50}{space 3}0.122{col 58}{space 4}-.3892892{col 71}{space 3} .0459376
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0179468{col 30}{space 2} .0135031{col 41}{space 1}    1.33{col 50}{space 3}0.184{col 58}{space 4}-.0085188{col 71}{space 3} .0444123
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1138651{col 30}{space 2} .0974236{col 41}{space 1}    1.17{col 50}{space 3}0.242{col 58}{space 4}-.0770816{col 71}{space 3} .3048118
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .8928645{col 30}{space 2} .3720828{col 41}{space 1}    2.40{col 50}{space 3}0.016{col 58}{space 4} .1635956{col 71}{space 3} 1.622133
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7374264{col 30}{space 2} .2404823{col 41}{space 1}    3.07{col 50}{space 3}0.002{col 58}{space 4} .2660897{col 71}{space 3} 1.208763
{txt}electricity_mean {c |}{col 18}{res}{space 2} .9954876{col 30}{space 2}  .257855{col 41}{space 1}    3.86{col 50}{space 3}0.000{col 58}{space 4}  .490101{col 71}{space 3} 1.500874
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2256852{col 30}{space 2} .2149943{col 41}{space 1}   -1.05{col 50}{space 3}0.294{col 58}{space 4}-.6470663{col 71}{space 3} .1956959
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0611335{col 30}{space 2} .2244245{col 41}{space 1}    0.27{col 50}{space 3}0.785{col 58}{space 4}-.3787305{col 71}{space 3} .5009975
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2}-.0684626{col 30}{space 2} .0825108{col 41}{space 1}   -0.83{col 50}{space 3}0.407{col 58}{space 4}-.2301808{col 71}{space 3} .0932555
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.0441671{col 30}{space 2} .1104979{col 41}{space 1}   -0.40{col 50}{space 3}0.689{col 58}{space 4}-.2607391{col 71}{space 3} .1724048
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0725426{col 30}{space 2} .0916233{col 41}{space 1}   -0.79{col 50}{space 3}0.429{col 58}{space 4}-.2521209{col 71}{space 3} .1070357
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0887909{col 30}{space 2} .0982753{col 41}{space 1}    0.90{col 50}{space 3}0.366{col 58}{space 4}-.1038251{col 71}{space 3} .2814069
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.209714{col 30}{space 2} .5109736{col 41}{space 1}   10.20{col 50}{space 3}0.000{col 58}{space 4} 4.208224{col 71}{space 3} 6.211204
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .77364729
         {txt}sigma_e {c |} {res} 1.1572423
             {txt}rho {c |} {res} .30888054{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     6,588
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,089

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0649                                         {txt}min = {res}         1
{txt}     between = {res}0.3144                                         {txt}avg = {res}       6.0
{txt}     overall = {res}0.1831                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}   938.86
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,089} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0344869{col 30}{space 2} .0202894{col 41}{space 1}    1.70{col 50}{space 3}0.089{col 58}{space 4}-.0052797{col 71}{space 3} .0742534
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0156558{col 30}{space 2} .0045571{col 41}{space 1}   -3.44{col 50}{space 3}0.001{col 58}{space 4}-.0245876{col 71}{space 3} -.006724
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0043245{col 30}{space 2} .0086142{col 41}{space 1}    0.50{col 50}{space 3}0.616{col 58}{space 4}-.0125591{col 71}{space 3} .0212081
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .092097{col 30}{space 2} .0926538{col 41}{space 1}    0.99{col 50}{space 3}0.320{col 58}{space 4}-.0895011{col 71}{space 3} .2736952
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0004683{col 30}{space 2} .0018488{col 41}{space 1}    0.25{col 50}{space 3}0.800{col 58}{space 4}-.0031552{col 71}{space 3} .0040919
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0049632{col 30}{space 2} .0563322{col 41}{space 1}   -0.09{col 50}{space 3}0.930{col 58}{space 4}-.1153723{col 71}{space 3} .1054459
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .277607{col 30}{space 2} .0522256{col 41}{space 1}    5.32{col 50}{space 3}0.000{col 58}{space 4} .1752467{col 71}{space 3} .3799673
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1891052{col 30}{space 2} .0752272{col 41}{space 1}    2.51{col 50}{space 3}0.012{col 58}{space 4} .0416627{col 71}{space 3} .3365478
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3061024{col 30}{space 2}  .051682{col 41}{space 1}    5.92{col 50}{space 3}0.000{col 58}{space 4} .2048074{col 71}{space 3} .4073973
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3635219{col 30}{space 2} .0525217{col 41}{space 1}    6.92{col 50}{space 3}0.000{col 58}{space 4} .2605812{col 71}{space 3} .4664626
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0367038{col 30}{space 2} .0423454{col 41}{space 1}    0.87{col 50}{space 3}0.386{col 58}{space 4}-.0462917{col 71}{space 3} .1196993
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1837131{col 30}{space 2}  .044669{col 41}{space 1}    4.11{col 50}{space 3}0.000{col 58}{space 4} .0961634{col 71}{space 3} .2712627
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0078151{col 30}{space 2} .0363594{col 41}{space 1}    0.21{col 50}{space 3}0.830{col 58}{space 4}-.0634481{col 71}{space 3} .0790783
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0016069{col 30}{space 2}  .001747{col 41}{space 1}    0.92{col 50}{space 3}0.358{col 58}{space 4}-.0018172{col 71}{space 3} .0050309
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0161177{col 30}{space 2} .0418475{col 41}{space 1}   -0.39{col 50}{space 3}0.700{col 58}{space 4}-.0981373{col 71}{space 3}  .065902
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1395579{col 30}{space 2} .1391069{col 41}{space 1}    1.00{col 50}{space 3}0.316{col 58}{space 4}-.1330866{col 71}{space 3} .4122024
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .2676196{col 30}{space 2} .1074504{col 41}{space 1}    2.49{col 50}{space 3}0.013{col 58}{space 4} .0570206{col 71}{space 3} .4782185
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4473403{col 30}{space 2} .1336006{col 41}{space 1}    3.35{col 50}{space 3}0.001{col 58}{space 4} .1854879{col 71}{space 3} .7091927
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0814083{col 30}{space 2} .0988567{col 41}{space 1}    0.82{col 50}{space 3}0.410{col 58}{space 4}-.1123473{col 71}{space 3} .2751638
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .295466{col 30}{space 2} .0908021{col 41}{space 1}    3.25{col 50}{space 3}0.001{col 58}{space 4} .1174972{col 71}{space 3} .4734348
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .1640479{col 30}{space 2} .0387564{col 41}{space 1}    4.23{col 50}{space 3}0.000{col 58}{space 4} .0880868{col 71}{space 3}  .240009
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1328776{col 30}{space 2}  .057383{col 41}{space 1}   -2.32{col 50}{space 3}0.021{col 58}{space 4}-.2453463{col 71}{space 3}-.0204089
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.1358538{col 30}{space 2} .0500764{col 41}{space 1}   -2.71{col 50}{space 3}0.007{col 58}{space 4}-.2340018{col 71}{space 3}-.0377058
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3619483{col 30}{space 2} .0498274{col 41}{space 1}    7.26{col 50}{space 3}0.000{col 58}{space 4} .2642885{col 71}{space 3} .4596081
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1451973{col 30}{space 2} .0501338{col 41}{space 1}    2.90{col 50}{space 3}0.004{col 58}{space 4} .0469369{col 71}{space 3} .2434577
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .3403017{col 30}{space 2} .0484037{col 41}{space 1}    7.03{col 50}{space 3}0.000{col 58}{space 4} .2454322{col 71}{space 3} .4351712
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.326643{col 30}{space 2} .2490087{col 41}{space 1}   13.36{col 50}{space 3}0.000{col 58}{space 4} 2.838595{col 71}{space 3} 3.814691
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69593919
         {txt}sigma_e {c |} {res} 1.2265638
             {txt}rho {c |} {res} .24353065{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S17_balance.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9_town    $xlist  pdd9_mean_town sum_town _cons)
{res}{txt}(note: file S17_balance.rtf not found)
(output written to {browse  `"S17_balance.rtf"'})

{com}. 
. 
. 
. 
. *                          dist_village_level                                  *
. 
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist i.country i.year   , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    30,867
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     9,851

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0336                                         {txt}min = {res}         1
{txt}     between = {res}0.4824                                         {txt}avg = {res}       3.1
{txt}     overall = {res}0.3277                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 11190.85
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:9,851} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0426649{col 30}{space 2} .0114697{col 41}{space 1}    3.72{col 50}{space 3}0.000{col 58}{space 4} .0201847{col 71}{space 3} .0651452
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0013712{col 30}{space 2} .0002142{col 41}{space 1}   -6.40{col 50}{space 3}0.000{col 58}{space 4} -.001791{col 71}{space 3}-.0009514
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0104867{col 30}{space 2} .0037294{col 41}{space 1}    2.81{col 50}{space 3}0.005{col 58}{space 4} .0031772{col 71}{space 3} .0177961
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0370813{col 30}{space 2} .0408627{col 41}{space 1}   -0.91{col 50}{space 3}0.364{col 58}{space 4}-.1171708{col 71}{space 3} .0430082
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0004148{col 30}{space 2} .0007047{col 41}{space 1}   -0.59{col 50}{space 3}0.556{col 58}{space 4} -.001796{col 71}{space 3} .0009664
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0249973{col 30}{space 2} .0251296{col 41}{space 1}   -0.99{col 50}{space 3}0.320{col 58}{space 4}-.0742505{col 71}{space 3} .0242558
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2678577{col 30}{space 2} .0209517{col 41}{space 1}   12.78{col 50}{space 3}0.000{col 58}{space 4} .2267932{col 71}{space 3} .3089223
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1368267{col 30}{space 2} .0430102{col 41}{space 1}    3.18{col 50}{space 3}0.001{col 58}{space 4} .0525284{col 71}{space 3} .2211251
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .162364{col 30}{space 2} .0254123{col 41}{space 1}    6.39{col 50}{space 3}0.000{col 58}{space 4} .1125569{col 71}{space 3} .2121712
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1410129{col 30}{space 2}  .030998{col 41}{space 1}    4.55{col 50}{space 3}0.000{col 58}{space 4}  .080258{col 71}{space 3} .2017678
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1142968{col 30}{space 2} .0288768{col 41}{space 1}    3.96{col 50}{space 3}0.000{col 58}{space 4} .0576994{col 71}{space 3} .1708942
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1625405{col 30}{space 2} .0246225{col 41}{space 1}    6.60{col 50}{space 3}0.000{col 58}{space 4} .1142813{col 71}{space 3} .2107998
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0852879{col 30}{space 2} .0192326{col 41}{space 1}   -4.43{col 50}{space 3}0.000{col 58}{space 4}-.1229831{col 71}{space 3}-.0475928
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0010383{col 30}{space 2}  .001361{col 41}{space 1}    0.76{col 50}{space 3}0.446{col 58}{space 4}-.0016292{col 71}{space 3} .0037059
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1342769{col 30}{space 2} .0225889{col 41}{space 1}    5.94{col 50}{space 3}0.000{col 58}{space 4} .0900036{col 71}{space 3} .1785503
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0617195{col 30}{space 2} .0643439{col 41}{space 1}    0.96{col 50}{space 3}0.337{col 58}{space 4}-.0643921{col 71}{space 3} .1878312
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5256645{col 30}{space 2} .0406946{col 41}{space 1}   12.92{col 50}{space 3}0.000{col 58}{space 4} .4459046{col 71}{space 3} .6054244
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6280509{col 30}{space 2} .0469932{col 41}{space 1}   13.36{col 50}{space 3}0.000{col 58}{space 4}  .535946{col 71}{space 3} .7201558
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3150368{col 30}{space 2} .0488876{col 41}{space 1}    6.44{col 50}{space 3}0.000{col 58}{space 4} .2192189{col 71}{space 3} .4108548
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .179462{col 30}{space 2} .0377996{col 41}{space 1}    4.75{col 50}{space 3}0.000{col 58}{space 4} .1053762{col 71}{space 3} .2535479
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .1085683{col 30}{space 2} .0159775{col 41}{space 1}    6.80{col 50}{space 3}0.000{col 58}{space 4} .0772531{col 71}{space 3} .1398836
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2} -.561002{col 30}{space 2} .0524956{col 41}{space 1}  -10.69{col 50}{space 3}0.000{col 58}{space 4}-.6638914{col 71}{space 3}-.4581125
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.547784{col 30}{space 2} .0472623{col 41}{space 1}  -32.75{col 50}{space 3}0.000{col 58}{space 4}-1.640417{col 71}{space 3}-1.455152
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.6233334{col 30}{space 2} .0510425{col 41}{space 1}  -12.21{col 50}{space 3}0.000{col 58}{space 4}-.7233748{col 71}{space 3}-.5232921
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.4083185{col 30}{space 2} .0750183{col 41}{space 1}   -5.44{col 50}{space 3}0.000{col 58}{space 4}-.5553516{col 71}{space 3}-.2612854
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .2781291{col 30}{space 2} .0543906{col 41}{space 1}    5.11{col 50}{space 3}0.000{col 58}{space 4} .1715255{col 71}{space 3} .3847326
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2058528{col 30}{space 2} .1000653{col 41}{space 1}   -2.06{col 50}{space 3}0.040{col 58}{space 4}-.4019773{col 71}{space 3}-.0097284
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}   .02612{col 30}{space 2} .0911252{col 41}{space 1}    0.29{col 50}{space 3}0.774{col 58}{space 4}-.1524821{col 71}{space 3} .2047221
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0493498{col 30}{space 2} .0919209{col 41}{space 1}    0.54{col 50}{space 3}0.591{col 58}{space 4}-.1308119{col 71}{space 3} .2295115
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0730359{col 30}{space 2} .0941932{col 41}{space 1}    0.78{col 50}{space 3}0.438{col 58}{space 4}-.1115794{col 71}{space 3} .2576511
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0862345{col 30}{space 2} .0923738{col 41}{space 1}    0.93{col 50}{space 3}0.351{col 58}{space 4}-.0948148{col 71}{space 3} .2672837
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.1820589{col 30}{space 2} .0947448{col 41}{space 1}   -1.92{col 50}{space 3}0.055{col 58}{space 4}-.3677552{col 71}{space 3} .0036374
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .2485657{col 30}{space 2} .0926623{col 41}{space 1}    2.68{col 50}{space 3}0.007{col 58}{space 4} .0669509{col 71}{space 3} .4301805
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.1789941{col 30}{space 2} .1026239{col 41}{space 1}   -1.74{col 50}{space 3}0.081{col 58}{space 4}-.3801333{col 71}{space 3}  .022145
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .5292188{col 30}{space 2} .0957092{col 41}{space 1}    5.53{col 50}{space 3}0.000{col 58}{space 4} .3416322{col 71}{space 3} .7168055
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .1455834{col 30}{space 2}  .093928{col 41}{space 1}    1.55{col 50}{space 3}0.121{col 58}{space 4}-.0385121{col 71}{space 3}  .329679
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2}  3.88295{col 30}{space 2}  .127502{col 41}{space 1}   30.45{col 50}{space 3}0.000{col 58}{space 4}  3.63305{col 71}{space 3} 4.132849
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .71407595
         {txt}sigma_e {c |} {res} 1.2200392
             {txt}rho {c |} {res} .25515633{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,299
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,149

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0242                                         {txt}min = {res}         1
{txt}     between = {res}0.3155                                         {txt}avg = {res}       3.0
{txt}     overall = {res}0.1996                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1676.42
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,149} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0704445{col 30}{space 2} .0170976{col 41}{space 1}    4.12{col 50}{space 3}0.000{col 58}{space 4} .0369339{col 71}{space 3} .1039551
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0055531{col 30}{space 2} .0006481{col 41}{space 1}   -8.57{col 50}{space 3}0.000{col 58}{space 4}-.0068234{col 71}{space 3}-.0042827
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0520738{col 30}{space 2} .0077148{col 41}{space 1}    6.75{col 50}{space 3}0.000{col 58}{space 4} .0369531{col 71}{space 3} .0671944
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0448804{col 30}{space 2}  .065003{col 41}{space 1}   -0.69{col 50}{space 3}0.490{col 58}{space 4}-.1722839{col 71}{space 3} .0825232
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0028697{col 30}{space 2} .0011003{col 41}{space 1}   -2.61{col 50}{space 3}0.009{col 58}{space 4}-.0050262{col 71}{space 3}-.0007131
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0376134{col 30}{space 2} .0407113{col 41}{space 1}   -0.92{col 50}{space 3}0.356{col 58}{space 4}-.1174061{col 71}{space 3} .0421793
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2940432{col 30}{space 2} .0334267{col 41}{space 1}    8.80{col 50}{space 3}0.000{col 58}{space 4} .2285281{col 71}{space 3} .3595584
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2466026{col 30}{space 2} .1595646{col 41}{space 1}   -1.55{col 50}{space 3}0.122{col 58}{space 4}-.5593435{col 71}{space 3} .0661383
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1945396{col 30}{space 2} .0388126{col 41}{space 1}    5.01{col 50}{space 3}0.000{col 58}{space 4} .1184684{col 71}{space 3} .2706108
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1293114{col 30}{space 2} .0481865{col 41}{space 1}    2.68{col 50}{space 3}0.007{col 58}{space 4} .0348676{col 71}{space 3} .2237552
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0664401{col 30}{space 2} .0722806{col 41}{space 1}    0.92{col 50}{space 3}0.358{col 58}{space 4}-.0752273{col 71}{space 3} .2081075
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1895504{col 30}{space 2} .0522542{col 41}{space 1}    3.63{col 50}{space 3}0.000{col 58}{space 4}  .087134{col 71}{space 3} .2919667
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1106794{col 30}{space 2} .0314466{col 41}{space 1}   -3.52{col 50}{space 3}0.000{col 58}{space 4}-.1723137{col 71}{space 3}-.0490452
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0145542{col 30}{space 2} .0039814{col 41}{space 1}    3.66{col 50}{space 3}0.000{col 58}{space 4} .0067508{col 71}{space 3} .0223576
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2189833{col 30}{space 2} .0325528{col 41}{space 1}    6.73{col 50}{space 3}0.000{col 58}{space 4} .1551809{col 71}{space 3} .2827857
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} 1.024768{col 30}{space 2} .2977612{col 41}{space 1}    3.44{col 50}{space 3}0.001{col 58}{space 4} .4411663{col 71}{space 3} 1.608369
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3852216{col 30}{space 2}  .061745{col 41}{space 1}    6.24{col 50}{space 3}0.000{col 58}{space 4} .2642036{col 71}{space 3} .5062396
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3879866{col 30}{space 2} .0758224{col 41}{space 1}    5.12{col 50}{space 3}0.000{col 58}{space 4} .2393775{col 71}{space 3} .5365957
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .5121212{col 30}{space 2} .1332752{col 41}{space 1}    3.84{col 50}{space 3}0.000{col 58}{space 4} .2509067{col 71}{space 3} .7733357
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1346331{col 30}{space 2} .0690753{col 41}{space 1}    1.95{col 50}{space 3}0.051{col 58}{space 4}-.0007521{col 71}{space 3} .2700182
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .1145654{col 30}{space 2} .0222225{col 41}{space 1}    5.16{col 50}{space 3}0.000{col 58}{space 4} .0710101{col 71}{space 3} .1581206
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1872869{col 30}{space 2} .0235893{col 41}{space 1}   -7.94{col 50}{space 3}0.000{col 58}{space 4}-.2335212{col 71}{space 3}-.1410527
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.313758{col 30}{space 2}  .117892{col 41}{space 1}   19.63{col 50}{space 3}0.000{col 58}{space 4} 2.082694{col 71}{space 3} 2.544822
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .66082174
         {txt}sigma_e {c |} {res} 1.0649195
             {txt}rho {c |} {res}  .2780127{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_MALAWI  if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,301
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,381

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0213                                         {txt}min = {res}         1
{txt}     between = {res}0.4100                                         {txt}avg = {res}       3.1
{txt}     overall = {res}0.2752                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1391.93
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,381} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} -.041608{col 30}{space 2} .0421858{col 41}{space 1}   -0.99{col 50}{space 3}0.324{col 58}{space 4}-.1242906{col 71}{space 3} .0410746
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0042663{col 30}{space 2} .0010373{col 41}{space 1}   -4.11{col 50}{space 3}0.000{col 58}{space 4}-.0062994{col 71}{space 3}-.0022331
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0025941{col 30}{space 2} .0116703{col 41}{space 1}    0.22{col 50}{space 3}0.824{col 58}{space 4}-.0202792{col 71}{space 3} .0254675
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2888779{col 30}{space 2} .1066665{col 41}{space 1}   -2.71{col 50}{space 3}0.007{col 58}{space 4}-.4979404{col 71}{space 3}-.0798154
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0012254{col 30}{space 2} .0018153{col 41}{space 1}   -0.68{col 50}{space 3}0.500{col 58}{space 4}-.0047833{col 71}{space 3} .0023326
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1088332{col 30}{space 2} .0625436{col 41}{space 1}   -1.74{col 50}{space 3}0.082{col 58}{space 4}-.2314165{col 71}{space 3} .0137501
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2978537{col 30}{space 2} .0603707{col 41}{space 1}    4.93{col 50}{space 3}0.000{col 58}{space 4} .1795293{col 71}{space 3} .4161781
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2209264{col 30}{space 2} .1965645{col 41}{space 1}    1.12{col 50}{space 3}0.261{col 58}{space 4}-.1643329{col 71}{space 3} .6061857
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0870587{col 30}{space 2}    .0713{col 41}{space 1}    1.22{col 50}{space 3}0.222{col 58}{space 4}-.0526867{col 71}{space 3}  .226804
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1565666{col 30}{space 2} .1429464{col 41}{space 1}    1.10{col 50}{space 3}0.273{col 58}{space 4}-.1236032{col 71}{space 3} .4367364
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1359443{col 30}{space 2} .0831479{col 41}{space 1}    1.63{col 50}{space 3}0.102{col 58}{space 4}-.0270227{col 71}{space 3} .2989112
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .237625{col 30}{space 2} .0576393{col 41}{space 1}    4.12{col 50}{space 3}0.000{col 58}{space 4}  .124654{col 71}{space 3} .3505959
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1817691{col 30}{space 2} .0446857{col 41}{space 1}   -4.07{col 50}{space 3}0.000{col 58}{space 4}-.2693515{col 71}{space 3}-.0941867
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0871638{col 30}{space 2} .0375108{col 41}{space 1}    2.32{col 50}{space 3}0.020{col 58}{space 4} .0136441{col 71}{space 3} .1606835
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0882564{col 30}{space 2} .0633929{col 41}{space 1}    1.39{col 50}{space 3}0.164{col 58}{space 4}-.0359913{col 71}{space 3} .2125042
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0251869{col 30}{space 2} .3185835{col 41}{space 1}   -0.08{col 50}{space 3}0.937{col 58}{space 4}-.6495991{col 71}{space 3} .5992253
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7495824{col 30}{space 2} .1127067{col 41}{space 1}    6.65{col 50}{space 3}0.000{col 58}{space 4} .5286814{col 71}{space 3} .9704834
{txt}electricity_mean {c |}{col 18}{res}{space 2} .9139216{col 30}{space 2} .1817029{col 41}{space 1}    5.03{col 50}{space 3}0.000{col 58}{space 4} .5577905{col 71}{space 3} 1.270053
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4122036{col 30}{space 2} .1186768{col 41}{space 1}    3.47{col 50}{space 3}0.001{col 58}{space 4} .1796014{col 71}{space 3} .6448057
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2980009{col 30}{space 2} .1046335{col 41}{space 1}    2.85{col 50}{space 3}0.004{col 58}{space 4}  .092923{col 71}{space 3} .5030789
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0005727{col 30}{space 2} .0679963{col 41}{space 1}    0.01{col 50}{space 3}0.993{col 58}{space 4}-.1326976{col 71}{space 3} .1338429
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .2290553{col 30}{space 2} .0587607{col 41}{space 1}    3.90{col 50}{space 3}0.000{col 58}{space 4} .1138863{col 71}{space 3} .3442242
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .1061368{col 30}{space 2}  .051216{col 41}{space 1}    2.07{col 50}{space 3}0.038{col 58}{space 4} .0057553{col 71}{space 3} .2065183
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.554801{col 30}{space 2} .3941771{col 41}{space 1}   14.09{col 50}{space 3}0.000{col 58}{space 4} 4.782228{col 71}{space 3} 6.327374
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .68406315
         {txt}sigma_e {c |} {res} 1.2920543
             {txt}rho {c |} {res} .21893611{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9 pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,552
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,853

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0237                                         {txt}min = {res}         1
{txt}     between = {res}0.2650                                         {txt}avg = {res}       1.9
{txt}     overall = {res}0.1755                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1102.32
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,853} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0281152{col 30}{space 2} .0443927{col 41}{space 1}    0.63{col 50}{space 3}0.527{col 58}{space 4}-.0588928{col 71}{space 3} .1151233
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2} .0001892{col 30}{space 2} .0003017{col 41}{space 1}    0.63{col 50}{space 3}0.531{col 58}{space 4}-.0004021{col 71}{space 3} .0007806
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0101871{col 30}{space 2} .0069129{col 41}{space 1}    1.47{col 50}{space 3}0.141{col 58}{space 4}-.0033619{col 71}{space 3} .0237361
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0873706{col 30}{space 2} .1116206{col 41}{space 1}   -0.78{col 50}{space 3}0.434{col 58}{space 4}-.3061429{col 71}{space 3} .1314016
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0024882{col 30}{space 2}  .001573{col 41}{space 1}    1.58{col 50}{space 3}0.114{col 58}{space 4}-.0005949{col 71}{space 3} .0055712
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0648473{col 30}{space 2} .0637171{col 41}{space 1}    1.02{col 50}{space 3}0.309{col 58}{space 4}-.0600358{col 71}{space 3} .1897305
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3052395{col 30}{space 2} .0501339{col 41}{space 1}    6.09{col 50}{space 3}0.000{col 58}{space 4} .2069789{col 71}{space 3} .4035002
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3435636{col 30}{space 2} .1114582{col 41}{space 1}    3.08{col 50}{space 3}0.002{col 58}{space 4} .1251095{col 71}{space 3} .5620176
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1323758{col 30}{space 2} .0792325{col 41}{space 1}    1.67{col 50}{space 3}0.095{col 58}{space 4}-.0229171{col 71}{space 3} .2876686
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2703096{col 30}{space 2}  .125239{col 41}{space 1}    2.16{col 50}{space 3}0.031{col 58}{space 4} .0248456{col 71}{space 3} .5157735
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2127946{col 30}{space 2} .0909441{col 41}{space 1}    2.34{col 50}{space 3}0.019{col 58}{space 4} .0345474{col 71}{space 3} .3910418
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1583424{col 30}{space 2} .0699705{col 41}{space 1}   -2.26{col 50}{space 3}0.024{col 58}{space 4} -.295482{col 71}{space 3}-.0212027
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1132619{col 30}{space 2} .0486097{col 41}{space 1}   -2.33{col 50}{space 3}0.020{col 58}{space 4}-.2085351{col 71}{space 3}-.0179887
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0004254{col 30}{space 2} .0017396{col 41}{space 1}   -0.24{col 50}{space 3}0.807{col 58}{space 4}-.0038349{col 71}{space 3} .0029841
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1465091{col 30}{space 2} .2368926{col 41}{space 1}    0.62{col 50}{space 3}0.536{col 58}{space 4}-.3177919{col 71}{space 3} .6108101
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0324636{col 30}{space 2} .1404805{col 41}{space 1}    0.23{col 50}{space 3}0.817{col 58}{space 4}-.2428732{col 71}{space 3} .3078004
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3544457{col 30}{space 2} .1013445{col 41}{space 1}    3.50{col 50}{space 3}0.000{col 58}{space 4} .1558142{col 71}{space 3} .5530773
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4513702{col 30}{space 2} .1451492{col 41}{space 1}    3.11{col 50}{space 3}0.002{col 58}{space 4}  .166883{col 71}{space 3} .7358574
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2137195{col 30}{space 2} .1177449{col 41}{space 1}    1.82{col 50}{space 3}0.070{col 58}{space 4}-.0170563{col 71}{space 3} .4444952
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4708497{col 30}{space 2} .0899764{col 41}{space 1}    5.23{col 50}{space 3}0.000{col 58}{space 4} .2944991{col 71}{space 3} .6472002
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2}  .078165{col 30}{space 2} .0547829{col 41}{space 1}    1.43{col 50}{space 3}0.154{col 58}{space 4}-.0292075{col 71}{space 3} .1855375
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2665879{col 30}{space 2} .0414918{col 41}{space 1}    6.43{col 50}{space 3}0.000{col 58}{space 4} .1852654{col 71}{space 3} .3479104
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.777185{col 30}{space 2}  .212653{col 41}{space 1}   17.76{col 50}{space 3}0.000{col 58}{space 4} 3.360392{col 71}{space 3} 4.193977
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .5432691
         {txt}sigma_e {c |} {res} 1.4004196
             {txt}rho {c |} {res}  .1308067{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,014
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,108

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0768                                         {txt}min = {res}         1
{txt}     between = {res}0.4141                                         {txt}avg = {res}       3.6
{txt}     overall = {res}0.2574                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1011.09
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,108} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .1650907{col 30}{space 2} .0333311{col 41}{space 1}    4.95{col 50}{space 3}0.000{col 58}{space 4}  .099763{col 71}{space 3} .2304184
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0055296{col 30}{space 2} .0007104{col 41}{space 1}   -7.78{col 50}{space 3}0.000{col 58}{space 4} -.006922{col 71}{space 3}-.0041372
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0026525{col 30}{space 2} .0083845{col 41}{space 1}    0.32{col 50}{space 3}0.752{col 58}{space 4}-.0137807{col 71}{space 3} .0190858
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0503109{col 30}{space 2} .1064201{col 41}{space 1}    0.47{col 50}{space 3}0.636{col 58}{space 4}-.1582687{col 71}{space 3} .2588905
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0060851{col 30}{space 2} .0019637{col 41}{space 1}    3.10{col 50}{space 3}0.002{col 58}{space 4} .0022362{col 71}{space 3} .0099339
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1555045{col 30}{space 2} .0748673{col 41}{space 1}    2.08{col 50}{space 3}0.038{col 58}{space 4} .0087674{col 71}{space 3} .3022417
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0887632{col 30}{space 2} .0504687{col 41}{space 1}    1.76{col 50}{space 3}0.079{col 58}{space 4}-.0101537{col 71}{space 3} .1876802
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0402401{col 30}{space 2} .0693046{col 41}{space 1}    0.58{col 50}{space 3}0.561{col 58}{space 4}-.0955944{col 71}{space 3} .1760746
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .190162{col 30}{space 2} .0669552{col 41}{space 1}    2.84{col 50}{space 3}0.005{col 58}{space 4} .0589323{col 71}{space 3} .3213918
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .147639{col 30}{space 2} .0859199{col 41}{space 1}    1.72{col 50}{space 3}0.086{col 58}{space 4}-.0207609{col 71}{space 3} .3160389
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2543054{col 30}{space 2} .0939078{col 41}{space 1}    2.71{col 50}{space 3}0.007{col 58}{space 4} .0702496{col 71}{space 3} .4383612
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2798959{col 30}{space 2} .0659509{col 41}{space 1}    4.24{col 50}{space 3}0.000{col 58}{space 4} .1506344{col 71}{space 3} .4091573
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0080991{col 30}{space 2} .0878439{col 41}{space 1}    0.09{col 50}{space 3}0.927{col 58}{space 4}-.1640718{col 71}{space 3} .1802701
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} -.000663{col 30}{space 2} .0133582{col 41}{space 1}   -0.05{col 50}{space 3}0.960{col 58}{space 4}-.0268446{col 71}{space 3} .0255185
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0781757{col 30}{space 2}  .113992{col 41}{space 1}    0.69{col 50}{space 3}0.493{col 58}{space 4}-.1452445{col 71}{space 3} .3015959
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0517196{col 30}{space 2} .1111027{col 41}{space 1}   -0.47{col 50}{space 3}0.642{col 58}{space 4}-.2694769{col 71}{space 3} .1660377
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .8639481{col 30}{space 2} .1272228{col 41}{space 1}    6.79{col 50}{space 3}0.000{col 58}{space 4} .6145961{col 71}{space 3}   1.1133
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7518812{col 30}{space 2} .1185375{col 41}{space 1}    6.34{col 50}{space 3}0.000{col 58}{space 4}  .519552{col 71}{space 3} .9842105
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0417843{col 30}{space 2} .1445067{col 41}{space 1}    0.29{col 50}{space 3}0.772{col 58}{space 4}-.2414437{col 71}{space 3} .3250122
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0525263{col 30}{space 2} .1041491{col 41}{space 1}   -0.50{col 50}{space 3}0.614{col 58}{space 4}-.2566549{col 71}{space 3} .1516022
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2}-.1307254{col 30}{space 2} .0580527{col 41}{space 1}   -2.25{col 50}{space 3}0.024{col 58}{space 4}-.2445067{col 71}{space 3}-.0169441
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.6093211{col 30}{space 2} .0646055{col 41}{space 1}   -9.43{col 50}{space 3}0.000{col 58}{space 4}-.7359456{col 71}{space 3}-.4826966
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.4626775{col 30}{space 2} .0643473{col 41}{space 1}   -7.19{col 50}{space 3}0.000{col 58}{space 4}-.5887959{col 71}{space 3}-.3365591
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3418848{col 30}{space 2} .0668402{col 41}{space 1}   -5.11{col 50}{space 3}0.000{col 58}{space 4}-.4728892{col 71}{space 3}-.2108804
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.746447{col 30}{space 2} .3731854{col 41}{space 1}   12.72{col 50}{space 3}0.000{col 58}{space 4} 4.015017{col 71}{space 3} 5.477877
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69369019
         {txt}sigma_e {c |} {res} 1.2335062
             {txt}rho {c |} {res} .24027343{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     1,113
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}       271

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0368                                         {txt}min = {res}         1
{txt}     between = {res}0.3586                                         {txt}avg = {res}       4.1
{txt}     overall = {res}0.2475                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}   236.86
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:271} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .1102233{col 30}{space 2} .0553673{col 41}{space 1}    1.99{col 50}{space 3}0.047{col 58}{space 4} .0017053{col 71}{space 3} .2187413
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0025953{col 30}{space 2} .0041377{col 41}{space 1}   -0.63{col 50}{space 3}0.531{col 58}{space 4} -.010705{col 71}{space 3} .0055145
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0471467{col 30}{space 2} .0212029{col 41}{space 1}   -2.22{col 50}{space 3}0.026{col 58}{space 4}-.0887036{col 71}{space 3}-.0055897
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .4132713{col 30}{space 2} .2206068{col 41}{space 1}    1.87{col 50}{space 3}0.061{col 58}{space 4}-.0191101{col 71}{space 3} .8456527
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0060496{col 30}{space 2} .0039833{col 41}{space 1}   -1.52{col 50}{space 3}0.129{col 58}{space 4}-.0138566{col 71}{space 3} .0017575
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3371714{col 30}{space 2} .1297265{col 41}{space 1}    2.60{col 50}{space 3}0.009{col 58}{space 4} .0829123{col 71}{space 3} .5914306
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1887334{col 30}{space 2} .1234254{col 41}{space 1}    1.53{col 50}{space 3}0.126{col 58}{space 4} -.053176{col 71}{space 3} .4306428
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2232532{col 30}{space 2}  .183289{col 41}{space 1}    1.22{col 50}{space 3}0.223{col 58}{space 4}-.1359866{col 71}{space 3}  .582493
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2791249{col 30}{space 2} .1194993{col 41}{space 1}    2.34{col 50}{space 3}0.020{col 58}{space 4} .0449106{col 71}{space 3} .5133392
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0926062{col 30}{space 2} .1270073{col 41}{space 1}   -0.73{col 50}{space 3}0.466{col 58}{space 4}-.3415359{col 71}{space 3} .1563235
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1098408{col 30}{space 2} .0950342{col 41}{space 1}    1.16{col 50}{space 3}0.248{col 58}{space 4}-.0764228{col 71}{space 3} .2961045
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2846613{col 30}{space 2} .1054171{col 41}{space 1}    2.70{col 50}{space 3}0.007{col 58}{space 4} .0780475{col 71}{space 3}  .491275
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1936408{col 30}{space 2} .1101575{col 41}{space 1}   -1.76{col 50}{space 3}0.079{col 58}{space 4}-.4095455{col 71}{space 3}  .022264
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0154452{col 30}{space 2} .0134347{col 41}{space 1}    1.15{col 50}{space 3}0.250{col 58}{space 4}-.0108864{col 71}{space 3} .0417768
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0844847{col 30}{space 2} .0970105{col 41}{space 1}    0.87{col 50}{space 3}0.384{col 58}{space 4}-.1056524{col 71}{space 3} .2746218
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .8149276{col 30}{space 2} .3604057{col 41}{space 1}    2.26{col 50}{space 3}0.024{col 58}{space 4} .1085453{col 71}{space 3}  1.52131
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7203671{col 30}{space 2} .2430905{col 41}{space 1}    2.96{col 50}{space 3}0.003{col 58}{space 4} .2439185{col 71}{space 3} 1.196816
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.094173{col 30}{space 2} .2504956{col 41}{space 1}    4.37{col 50}{space 3}0.000{col 58}{space 4} .6032105{col 71}{space 3} 1.585135
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2268417{col 30}{space 2} .2169028{col 41}{space 1}   -1.05{col 50}{space 3}0.296{col 58}{space 4}-.6519633{col 71}{space 3}   .19828
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0720696{col 30}{space 2} .2260324{col 41}{space 1}    0.32{col 50}{space 3}0.750{col 58}{space 4}-.3709457{col 71}{space 3}  .515085
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2}-.0630504{col 30}{space 2} .1089235{col 41}{space 1}   -0.58{col 50}{space 3}0.563{col 58}{space 4}-.2765365{col 71}{space 3} .1504357
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.0378705{col 30}{space 2} .1132342{col 41}{space 1}   -0.33{col 50}{space 3}0.738{col 58}{space 4}-.2598056{col 71}{space 3} .1840645
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0841766{col 30}{space 2} .0913448{col 41}{space 1}   -0.92{col 50}{space 3}0.357{col 58}{space 4}-.2632091{col 71}{space 3} .0948558
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0929893{col 30}{space 2} .0981959{col 41}{space 1}    0.95{col 50}{space 3}0.344{col 58}{space 4}-.0994711{col 71}{space 3} .2854496
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.577999{col 30}{space 2} .7029767{col 41}{space 1}    6.51{col 50}{space 3}0.000{col 58}{space 4}  3.20019{col 71}{space 3} 5.955808
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .80175455
         {txt}sigma_e {c |} {res} 1.1550411
             {txt}rho {c |} {res} .32515581{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     6,588
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,089

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0660                                         {txt}min = {res}         1
{txt}     between = {res}0.3174                                         {txt}avg = {res}       6.0
{txt}     overall = {res}0.1836                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}   917.21
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,089} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0519661{col 30}{space 2} .0242736{col 41}{space 1}    2.14{col 50}{space 3}0.032{col 58}{space 4} .0043907{col 71}{space 3} .0995415
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}  .001587{col 30}{space 2} .0014216{col 41}{space 1}    1.12{col 50}{space 3}0.264{col 58}{space 4}-.0011992{col 71}{space 3} .0043732
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0078886{col 30}{space 2} .0086225{col 41}{space 1}    0.91{col 50}{space 3}0.360{col 58}{space 4}-.0090111{col 71}{space 3} .0247883
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0953533{col 30}{space 2} .0923455{col 41}{space 1}    1.03{col 50}{space 3}0.302{col 58}{space 4}-.0856406{col 71}{space 3} .2763471
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0002617{col 30}{space 2} .0018463{col 41}{space 1}    0.14{col 50}{space 3}0.887{col 58}{space 4}-.0033569{col 71}{space 3} .0038803
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0112763{col 30}{space 2} .0558731{col 41}{space 1}   -0.20{col 50}{space 3}0.840{col 58}{space 4}-.1207857{col 71}{space 3}  .098233
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2704815{col 30}{space 2} .0520683{col 41}{space 1}    5.19{col 50}{space 3}0.000{col 58}{space 4} .1684295{col 71}{space 3} .3725334
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1861216{col 30}{space 2} .0751199{col 41}{space 1}    2.48{col 50}{space 3}0.013{col 58}{space 4} .0388893{col 71}{space 3}  .333354
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3018804{col 30}{space 2} .0516922{col 41}{space 1}    5.84{col 50}{space 3}0.000{col 58}{space 4} .2005655{col 71}{space 3} .4031953
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3546099{col 30}{space 2} .0525352{col 41}{space 1}    6.75{col 50}{space 3}0.000{col 58}{space 4} .2516429{col 71}{space 3}  .457577
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0384723{col 30}{space 2} .0422509{col 41}{space 1}    0.91{col 50}{space 3}0.363{col 58}{space 4}-.0443379{col 71}{space 3} .1212825
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1826634{col 30}{space 2} .0446651{col 41}{space 1}    4.09{col 50}{space 3}0.000{col 58}{space 4} .0951215{col 71}{space 3} .2702053
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}  .029592{col 30}{space 2} .0364338{col 41}{space 1}    0.81{col 50}{space 3}0.417{col 58}{space 4}-.0418169{col 71}{space 3} .1010008
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}   .00208{col 30}{space 2} .0018644{col 41}{space 1}    1.12{col 50}{space 3}0.265{col 58}{space 4}-.0015741{col 71}{space 3} .0057342
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0092153{col 30}{space 2}  .041834{col 41}{space 1}   -0.22{col 50}{space 3}0.826{col 58}{space 4}-.0912085{col 71}{space 3} .0727779
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1869541{col 30}{space 2} .1412383{col 41}{space 1}    1.32{col 50}{space 3}0.186{col 58}{space 4}-.0898678{col 71}{space 3}  .463776
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .2457569{col 30}{space 2} .1061972{col 41}{space 1}    2.31{col 50}{space 3}0.021{col 58}{space 4} .0376142{col 71}{space 3} .4538995
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3807281{col 30}{space 2} .1332712{col 41}{space 1}    2.86{col 50}{space 3}0.004{col 58}{space 4} .1195213{col 71}{space 3} .6419349
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0640432{col 30}{space 2} .0998542{col 41}{space 1}    0.64{col 50}{space 3}0.521{col 58}{space 4}-.1316673{col 71}{space 3} .2597538
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3061844{col 30}{space 2} .0902051{col 41}{space 1}    3.39{col 50}{space 3}0.001{col 58}{space 4} .1293856{col 71}{space 3} .4829832
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .1732553{col 30}{space 2} .0528537{col 41}{space 1}    3.28{col 50}{space 3}0.001{col 58}{space 4} .0696639{col 71}{space 3} .2768468
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1313994{col 30}{space 2} .0573798{col 41}{space 1}   -2.29{col 50}{space 3}0.022{col 58}{space 4}-.2438618{col 71}{space 3}-.0189369
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.1461736{col 30}{space 2} .0506538{col 41}{space 1}   -2.89{col 50}{space 3}0.004{col 58}{space 4}-.2454532{col 71}{space 3} -.046894
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3395394{col 30}{space 2} .0499852{col 41}{space 1}    6.79{col 50}{space 3}0.000{col 58}{space 4} .2415702{col 71}{space 3} .4375085
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1160968{col 30}{space 2} .0497389{col 41}{space 1}    2.33{col 50}{space 3}0.020{col 58}{space 4} .0186103{col 71}{space 3} .2135832
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .3258809{col 30}{space 2} .0484117{col 41}{space 1}    6.73{col 50}{space 3}0.000{col 58}{space 4} .2309958{col 71}{space 3}  .420766
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.727848{col 30}{space 2} .3586988{col 41}{space 1}    7.60{col 50}{space 3}0.000{col 58}{space 4} 2.024811{col 71}{space 3} 3.430885
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69577612
         {txt}sigma_e {c |} {res} 1.2259104
             {txt}rho {c |} {res} .24364064{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S18_balance.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9_dist    $xlist  pdd9_mean_dist sum_dist _cons)
{res}{txt}(note: file S18_balance.rtf not found)
(output written to {browse  `"S18_balance.rtf"'})

{com}. restore
{txt}
{com}. 
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. ********************************************************************************
. *                 Balanced sample with Heckman selection correction
. ********************************************************************************
. use  NER_panel_data.dta, clear
{txt}
{com}. gen country=1
{txt}
{com}. append using NIGERIA_panel_data.dta
{txt}
{com}. replace country=2 if country ==.
{txt}(18,592 real changes made)

{com}. 
. append using ETHIOPIA_panel_data.dta
{txt}
{com}. replace country=3 if country ==.
{txt}(13,511 real changes made)

{com}. 
. append using UGA_panel_data.dta
{txt}
{com}. replace country=4 if country ==.
{txt}(20,313 real changes made)

{com}. 
. append using TZA_panel_data.dta
{txt}
{com}. replace country=5 if country ==.
{txt}(21,117 real changes made)

{com}. 
. append using MWI_panel_data.dta
{txt}
{com}. replace country=6 if country ==.
{txt}(9,163 real changes made)

{com}. 
. xtset HHID_panel year
{res}{txt}{col 8}panel variable:  {res}HHID_panel (unbalanced)
{txt}{col 9}time variable:  {res}{col 25}year, 2008 to 2019, but with gaps
{txt}{col 17}delta:  {res}1 unit
{txt}
{com}. 
. label define country 1 "Niger" 2 "Nigeria" 3 "Ethiopia" 4 "Uganda" 5 "Tanzania" 6 "Malawi"
{txt}
{com}. label values country country
{txt}
{com}. 
. 
. gen dyear=1
{txt}
{com}. egen total_year=sum(dyear), by(HHID_panel)
{txt}
{com}. 
. gen balance=0
{txt}
{com}. replace balance=1 if total_year==2&country==1
{txt}(5,954 real changes made)

{com}. replace balance=1 if total_year==4&country==2
{txt}(4,812 real changes made)

{com}. replace balance=1 if total_year==3&country==3
{txt}(9,447 real changes made)

{com}. replace balance=1 if total_year==7&country==4
{txt}(7,805 real changes made)

{com}. replace balance=1 if total_year==5&country==5
{txt}(1,585 real changes made)

{com}. replace balance=1 if total_year==4&country==6
{txt}(5,604 real changes made)

{com}. tab country year

           {txt}{c |}                                                           year
   country {c |}      2008       2009       2010       2011       2012       2013       2014       2015       2016       2018       2019 {c |}     Total
{hline 11}{c +}{hline 121}{c +}{hline 10}
     Niger {c |}{res}         0          0          0      3,930          0          0      3,116          0          0          0          0 {txt}{c |}{res}     7,046 
{txt}   Nigeria {c |}{res}         0          0      4,801          0      4,724          0          0      4,504          0      4,563          0 {txt}{c |}{res}    18,592 
{txt}  Ethiopia {c |}{res}         0          0          0      3,786          0      5,037          0      4,688          0          0          0 {txt}{c |}{res}    13,511 
{txt}    Uganda {c |}{res}         0      2,837      2,570      2,751          0      3,028          0      3,131          0      3,052      2,944 {txt}{c |}{res}    20,313 
{txt}  Tanzania {c |}{res}     3,176          0      3,767          0      4,705          0      4,182          0          0          0      5,287 {txt}{c |}{res}    21,117 
{txt}    Malawi {c |}{res}         0          0      1,581          0          0      1,962          0          0      2,447          0      3,173 {txt}{c |}{res}     9,163 
{txt}{hline 11}{c +}{hline 121}{c +}{hline 10}
     Total {c |}{res}     3,176      2,837     12,719     10,467      9,429     10,027      7,298     12,323      2,447      7,615     11,404 {txt}{c |}{res}    89,742 
{txt}
{com}. 
. egen mean_balance=mean(balance), by(country year)
{txt}
{com}. 
. probit balance pdd9 hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop mean_balance i.country i.year

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-60106.653}  
Iteration 1:{space 3}log likelihood = {res:-42907.524}  
Iteration 2:{space 3}log likelihood = {res:-42708.349}  
Iteration 3:{space 3}log likelihood = {res:-42708.178}  
Iteration 4:{space 3}log likelihood = {res:-42708.178}  
{res}
{txt}Probit regression{col 49}Number of obs{col 67}= {res}    89,742
{txt}{col 49}LR chi2({res}30{txt}){col 67}= {res}  34796.95
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-42708.178{txt}{col 49}Pseudo R2{col 67}= {res}    0.2895

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        balance{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .1294109{col 29}{space 2} .0032604{col 40}{space 1}   39.69{col 49}{space 3}0.000{col 57}{space 4} .1230207{col 70}{space 3}  .135801
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0408369{col 29}{space 2} .0018714{col 40}{space 1}   21.82{col 49}{space 3}0.000{col 57}{space 4} .0371691{col 70}{space 3} .0445046
{txt}dependent_share {c |}{col 17}{res}{space 2} .0014998{col 29}{space 2} .0214251{col 40}{space 1}    0.07{col 49}{space 3}0.944{col 57}{space 4}-.0404927{col 70}{space 3} .0434923
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0099266{col 29}{space 2} .0003428{col 40}{space 1}   28.96{col 49}{space 3}0.000{col 57}{space 4} .0092547{col 70}{space 3} .0105985
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.0052385{col 29}{space 2} .0123504{col 40}{space 1}   -0.42{col 49}{space 3}0.671{col 57}{space 4}-.0294449{col 70}{space 3} .0189679
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .0230621{col 29}{space 2} .0120798{col 40}{space 1}    1.91{col 49}{space 3}0.056{col 57}{space 4}-.0006138{col 70}{space 3}  .046738
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .0249783{col 29}{space 2} .0156627{col 40}{space 1}    1.59{col 49}{space 3}0.111{col 57}{space 4}-.0057201{col 70}{space 3} .0556767
{txt}{space 10}phone {c |}{col 17}{res}{space 2}-.0724177{col 29}{space 2} .0120933{col 40}{space 1}   -5.99{col 49}{space 3}0.000{col 57}{space 4}-.0961201{col 70}{space 3}-.0487154
{txt}{space 4}electricity {c |}{col 17}{res}{space 2}-.1488268{col 29}{space 2} .0126281{col 40}{space 1}  -11.79{col 49}{space 3}0.000{col 57}{space 4}-.1735774{col 70}{space 3}-.1240762
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2}-.0287723{col 29}{space 2} .0117547{col 40}{space 1}   -2.45{col 49}{space 3}0.014{col 57}{space 4} -.051811{col 70}{space 3}-.0057336
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2}   .04616{col 29}{space 2} .0104731{col 40}{space 1}    4.41{col 49}{space 3}0.000{col 57}{space 4} .0256331{col 70}{space 3} .0666868
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0313433{col 29}{space 2} .0130055{col 40}{space 1}    2.41{col 49}{space 3}0.016{col 57}{space 4}  .005853{col 70}{space 3} .0568336
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2}-.0056668{col 29}{space 2} .0009884{col 40}{space 1}   -5.73{col 49}{space 3}0.000{col 57}{space 4}-.0076041{col 70}{space 3}-.0037296
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .2001328{col 29}{space 2} .0137236{col 40}{space 1}   14.58{col 49}{space 3}0.000{col 57}{space 4}  .173235{col 70}{space 3} .2270306
{txt}{space 3}mean_balance {c |}{col 17}{res}{space 2} 3.401437{col 29}{space 2} .0907475{col 40}{space 1}   37.48{col 49}{space 3}0.000{col 57}{space 4} 3.223576{col 70}{space 3} 3.579299
{txt}{space 15} {c |}
{space 8}country {c |}
{space 7}Nigeria  {c |}{col 17}{res}{space 2} .1683203{col 29}{space 2} .0538319{col 40}{space 1}    3.13{col 49}{space 3}0.002{col 57}{space 4} .0628118{col 70}{space 3} .2738288
{txt}{space 6}Ethiopia  {c |}{col 17}{res}{space 2}-.1121071{col 29}{space 2} .0285914{col 40}{space 1}   -3.92{col 49}{space 3}0.000{col 57}{space 4}-.1681452{col 70}{space 3}-.0560691
{txt}{space 8}Uganda  {c |}{col 17}{res}{space 2}-.0680811{col 29}{space 2} .0422798{col 40}{space 1}   -1.61{col 49}{space 3}0.107{col 57}{space 4}-.1509481{col 70}{space 3} .0147858
{txt}{space 6}Tanzania  {c |}{col 17}{res}{space 2}-.2113553{col 29}{space 2}  .069039{col 40}{space 1}   -3.06{col 49}{space 3}0.002{col 57}{space 4}-.3466693{col 70}{space 3}-.0760414
{txt}{space 8}Malawi  {c |}{col 17}{res}{space 2}-.0785701{col 29}{space 2}  .034486{col 40}{space 1}   -2.28{col 49}{space 3}0.023{col 57}{space 4}-.1461614{col 70}{space 3}-.0109788
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}2009  {c |}{col 17}{res}{space 2}-.1674862{col 29}{space 2} .0452638{col 40}{space 1}   -3.70{col 49}{space 3}0.000{col 57}{space 4}-.2562016{col 70}{space 3}-.0787708
{txt}{space 10}2010  {c |}{col 17}{res}{space 2}-.0997003{col 29}{space 2} .0373997{col 40}{space 1}   -2.67{col 49}{space 3}0.008{col 57}{space 4}-.1730025{col 70}{space 3}-.0263982
{txt}{space 10}2011  {c |}{col 17}{res}{space 2}-.1855541{col 29}{space 2} .0404346{col 40}{space 1}   -4.59{col 49}{space 3}0.000{col 57}{space 4}-.2648045{col 70}{space 3}-.1063038
{txt}{space 10}2012  {c |}{col 17}{res}{space 2}-.1143467{col 29}{space 2}  .038411{col 40}{space 1}   -2.98{col 49}{space 3}0.003{col 57}{space 4}-.1896309{col 70}{space 3}-.0390625
{txt}{space 10}2013  {c |}{col 17}{res}{space 2}-.1021905{col 29}{space 2} .0405422{col 40}{space 1}   -2.52{col 49}{space 3}0.012{col 57}{space 4}-.1816517{col 70}{space 3}-.0227292
{txt}{space 10}2014  {c |}{col 17}{res}{space 2} .0503749{col 29}{space 2} .0411004{col 40}{space 1}    1.23{col 49}{space 3}0.220{col 57}{space 4}-.0301803{col 70}{space 3} .1309301
{txt}{space 10}2015  {c |}{col 17}{res}{space 2} -.091663{col 29}{space 2} .0395214{col 40}{space 1}   -2.32{col 49}{space 3}0.020{col 57}{space 4}-.1691234{col 70}{space 3}-.0142025
{txt}{space 10}2016  {c |}{col 17}{res}{space 2}-.0681702{col 29}{space 2}  .049538{col 40}{space 1}   -1.38{col 49}{space 3}0.169{col 57}{space 4} -.165263{col 70}{space 3} .0289225
{txt}{space 10}2018  {c |}{col 17}{res}{space 2}-.0613351{col 29}{space 2} .0402936{col 40}{space 1}   -1.52{col 49}{space 3}0.128{col 57}{space 4} -.140309{col 70}{space 3} .0176389
{txt}{space 10}2019  {c |}{col 17}{res}{space 2}-.0202295{col 29}{space 2} .0398112{col 40}{space 1}   -0.51{col 49}{space 3}0.611{col 57}{space 4}-.0982581{col 70}{space 3}  .057799
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}-2.523689{col 29}{space 2} .0866462{col 40}{space 1}  -29.13{col 49}{space 3}0.000{col 57}{space 4}-2.693512{col 70}{space 3}-2.353865
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. predict xb, xb
{txt}
{com}. gen double imr = normalden(xb)/normal(xb)
{txt}
{com}. keep if balance==1
{txt}(54,535 observations deleted)

{com}. 
. 
. foreach x of varlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop hdd9 pdd9 no_species{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. 
. 
. 
. tab year, generate(year_)

       {txt}year {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
       2008 {c |}{res}        317        0.90        0.90
{txt}       2009 {c |}{res}      1,115        3.17        4.07
{txt}       2010 {c |}{res}      4,036       11.46       15.53
{txt}       2011 {c |}{res}      7,241       20.57       36.10
{txt}       2012 {c |}{res}      1,520        4.32       40.42
{txt}       2013 {c |}{res}      5,665       16.09       56.51
{txt}       2014 {c |}{res}      3,294        9.36       65.86
{txt}       2015 {c |}{res}      5,467       15.53       81.39
{txt}       2016 {c |}{res}      1,401        3.98       85.37
{txt}       2018 {c |}{res}      2,318        6.58       91.95
{txt}       2019 {c |}{res}      2,833        8.05      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}     35,207      100.00
{txt}
{com}. global year_NIGER year_4
{txt}
{com}. global year_NIGERIA year_3 year_5 year_8
{txt}
{com}. global year_ETHIOPIA year_6
{txt}
{com}. global year_UGANDA   year_3 year_4 year_6 year_8 year_10
{txt}
{com}. global year_TANZANIA year_1 year_5 year_7
{txt}
{com}. global year_MALAWI year_3 year_6 
{txt}
{com}. global xlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop  motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean  imr
{txt}
{com}. 
. 
. 
. 
. 
. 
. 
. ********************************************************************************
. *                                   S11                                        *
. ********************************************************************************
. eststo clear
{txt}
{com}. xtreg hdd9  no_species   $xlist  no_species_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    35,207
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    10,162

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0402                                         {txt}min = {res}         2
{txt}     between = {res}0.5093                                         {txt}avg = {res}       3.5
{txt}     overall = {res}0.3456                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 13118.44
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:10,162} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2}  .028423{col 30}{space 2} .0041036{col 41}{space 1}    6.93{col 50}{space 3}0.000{col 58}{space 4}   .02038{col 71}{space 3}  .036466
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0068699{col 30}{space 2} .0038148{col 41}{space 1}   -1.80{col 50}{space 3}0.072{col 58}{space 4}-.0143468{col 71}{space 3}  .000607
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0025396{col 30}{space 2} .0384214{col 41}{space 1}   -0.07{col 50}{space 3}0.947{col 58}{space 4}-.0778442{col 71}{space 3}  .072765
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0025472{col 30}{space 2} .0007463{col 41}{space 1}   -3.41{col 50}{space 3}0.001{col 58}{space 4}  -.00401{col 71}{space 3}-.0010844
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0090522{col 30}{space 2} .0238262{col 41}{space 1}   -0.38{col 50}{space 3}0.704{col 58}{space 4}-.0557507{col 71}{space 3} .0376463
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2438163{col 30}{space 2}  .020306{col 41}{space 1}   12.01{col 50}{space 3}0.000{col 58}{space 4} .2040172{col 71}{space 3} .2836154
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1335874{col 30}{space 2} .0383433{col 41}{space 1}    3.48{col 50}{space 3}0.000{col 58}{space 4} .0584359{col 71}{space 3}  .208739
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1795877{col 30}{space 2}   .02415{col 41}{space 1}    7.44{col 50}{space 3}0.000{col 58}{space 4} .1322546{col 71}{space 3} .2269207
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2000906{col 30}{space 2} .0290644{col 41}{space 1}    6.88{col 50}{space 3}0.000{col 58}{space 4} .1431254{col 71}{space 3} .2570558
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1457886{col 30}{space 2} .0260421{col 41}{space 1}    5.60{col 50}{space 3}0.000{col 58}{space 4}  .094747{col 71}{space 3} .1968302
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1698409{col 30}{space 2} .0224045{col 41}{space 1}    7.58{col 50}{space 3}0.000{col 58}{space 4} .1259289{col 71}{space 3} .2137529
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.103034{col 30}{space 2} .0183663{col 41}{space 1}   -5.61{col 50}{space 3}0.000{col 58}{space 4}-.1390312{col 71}{space 3}-.0670367
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0008848{col 30}{space 2} .0013157{col 41}{space 1}    0.67{col 50}{space 3}0.501{col 58}{space 4}-.0016939{col 71}{space 3} .0034636
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0331973{col 30}{space 2} .0233393{col 41}{space 1}    1.42{col 50}{space 3}0.155{col 58}{space 4} -.012547{col 71}{space 3} .0789415
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0037497{col 30}{space 2} .0594188{col 41}{space 1}    0.06{col 50}{space 3}0.950{col 58}{space 4}-.1127089{col 71}{space 3} .1202084
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5771161{col 30}{space 2} .0397693{col 41}{space 1}   14.51{col 50}{space 3}0.000{col 58}{space 4} .4991698{col 71}{space 3} .6550624
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7430916{col 30}{space 2} .0459263{col 41}{space 1}   16.18{col 50}{space 3}0.000{col 58}{space 4} .6530776{col 71}{space 3} .8331055
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3814392{col 30}{space 2} .0461134{col 41}{space 1}    8.27{col 50}{space 3}0.000{col 58}{space 4} .2910586{col 71}{space 3} .4718198
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2094251{col 30}{space 2} .0361887{col 41}{space 1}    5.79{col 50}{space 3}0.000{col 58}{space 4} .1384965{col 71}{space 3} .2803536
{txt}{space 13}imr {c |}{col 18}{res}{space 2} -.364017{col 30}{space 2} .0614865{col 41}{space 1}   -5.92{col 50}{space 3}0.000{col 58}{space 4}-.4845282{col 71}{space 3}-.2435057
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2} .0029934{col 30}{space 2} .0053352{col 41}{space 1}    0.56{col 50}{space 3}0.575{col 58}{space 4}-.0074633{col 71}{space 3} .0134502
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.0862299{col 30}{space 2} .0676058{col 41}{space 1}   -1.28{col 50}{space 3}0.202{col 58}{space 4}-.2187349{col 71}{space 3} .0462752
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}   -1.442{col 30}{space 2} .0399868{col 41}{space 1}  -36.06{col 50}{space 3}0.000{col 58}{space 4}-1.520372{col 71}{space 3}-1.363627
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.2502897{col 30}{space 2} .0535823{col 41}{space 1}   -4.67{col 50}{space 3}0.000{col 58}{space 4} -.355309{col 71}{space 3}-.1452703
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2} .3174541{col 30}{space 2}  .113246{col 41}{space 1}    2.80{col 50}{space 3}0.005{col 58}{space 4} .0954959{col 71}{space 3} .5394122
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .5524758{col 30}{space 2} .0459006{col 41}{space 1}   12.04{col 50}{space 3}0.000{col 58}{space 4} .4625124{col 71}{space 3} .6424393
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.1497844{col 30}{space 2} .0909207{col 41}{space 1}   -1.65{col 50}{space 3}0.099{col 58}{space 4}-.3279857{col 71}{space 3} .0284169
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0447399{col 30}{space 2} .0814264{col 41}{space 1}   -0.55{col 50}{space 3}0.583{col 58}{space 4}-.2043327{col 71}{space 3} .1148529
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .1255652{col 30}{space 2} .0829399{col 41}{space 1}    1.51{col 50}{space 3}0.130{col 58}{space 4}-.0369941{col 71}{space 3} .2881245
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .1201123{col 30}{space 2} .0841177{col 41}{space 1}    1.43{col 50}{space 3}0.153{col 58}{space 4}-.0447554{col 71}{space 3}   .28498
{txt}{space 11}2013  {c |}{col 18}{res}{space 2}  .176251{col 30}{space 2} .0844826{col 41}{space 1}    2.09{col 50}{space 3}0.037{col 58}{space 4} .0106681{col 71}{space 3} .3418339
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.1688656{col 30}{space 2} .0860042{col 41}{space 1}   -1.96{col 50}{space 3}0.050{col 58}{space 4}-.3374307{col 71}{space 3}-.0003005
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .3068887{col 30}{space 2} .0842718{col 41}{space 1}    3.64{col 50}{space 3}0.000{col 58}{space 4}  .141719{col 71}{space 3} .4720584
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.0055469{col 30}{space 2} .0941586{col 41}{space 1}   -0.06{col 50}{space 3}0.953{col 58}{space 4}-.1900943{col 71}{space 3} .1790006
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .5835648{col 30}{space 2} .0866254{col 41}{space 1}    6.74{col 50}{space 3}0.000{col 58}{space 4} .4137821{col 71}{space 3} .7533476
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .2779052{col 30}{space 2} .0880113{col 41}{space 1}    3.16{col 50}{space 3}0.002{col 58}{space 4} .1054061{col 71}{space 3} .4504042
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2}  4.74928{col 30}{space 2} .1069886{col 41}{space 1}   44.39{col 50}{space 3}0.000{col 58}{space 4} 4.539587{col 71}{space 3} 4.958974
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .70851748
         {txt}sigma_e {c |} {res} 1.2296613
             {txt}rho {c |} {res} .24924583{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,447
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,149

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0241                                         {txt}min = {res}         3
{txt}     between = {res}0.2890                                         {txt}avg = {res}       3.0
{txt}     overall = {res}0.1840                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1434.89
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,149} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0212624{col 30}{space 2} .0057488{col 41}{space 1}    3.70{col 50}{space 3}0.000{col 58}{space 4} .0099949{col 71}{space 3} .0325298
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0406009{col 30}{space 2} .0083893{col 41}{space 1}    4.84{col 50}{space 3}0.000{col 58}{space 4} .0241581{col 71}{space 3} .0570436
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0083552{col 30}{space 2} .0650116{col 41}{space 1}   -0.13{col 50}{space 3}0.898{col 58}{space 4}-.1357756{col 71}{space 3} .1190653
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.002366{col 30}{space 2} .0012187{col 41}{space 1}   -1.94{col 50}{space 3}0.052{col 58}{space 4}-.0047546{col 71}{space 3} .0000226
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0193666{col 30}{space 2} .0414777{col 41}{space 1}    0.47{col 50}{space 3}0.641{col 58}{space 4}-.0619282{col 71}{space 3} .1006613
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3230476{col 30}{space 2} .0335167{col 41}{space 1}    9.64{col 50}{space 3}0.000{col 58}{space 4} .2573561{col 71}{space 3} .3887391
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} -.188314{col 30}{space 2} .1576418{col 41}{space 1}   -1.19{col 50}{space 3}0.232{col 58}{space 4}-.4972863{col 71}{space 3} .1206583
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1816193{col 30}{space 2} .0401599{col 41}{space 1}    4.52{col 50}{space 3}0.000{col 58}{space 4} .1029072{col 71}{space 3} .2603313
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0971076{col 30}{space 2} .0501964{col 41}{space 1}    1.93{col 50}{space 3}0.053{col 58}{space 4}-.0012755{col 71}{space 3} .1954907
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .064248{col 30}{space 2} .0712421{col 41}{space 1}    0.90{col 50}{space 3}0.367{col 58}{space 4}-.0753839{col 71}{space 3} .2038799
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2174402{col 30}{space 2} .0515565{col 41}{space 1}    4.22{col 50}{space 3}0.000{col 58}{space 4} .1163914{col 71}{space 3} .3184891
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1586245{col 30}{space 2} .0313547{col 41}{space 1}   -5.06{col 50}{space 3}0.000{col 58}{space 4}-.2200787{col 71}{space 3}-.0971703
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0101087{col 30}{space 2} .0037693{col 41}{space 1}    2.68{col 50}{space 3}0.007{col 58}{space 4} .0027211{col 71}{space 3} .0174964
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2480769{col 30}{space 2} .0357026{col 41}{space 1}    6.95{col 50}{space 3}0.000{col 58}{space 4} .1781011{col 71}{space 3} .3180527
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} 1.097043{col 30}{space 2} .3078941{col 41}{space 1}    3.56{col 50}{space 3}0.000{col 58}{space 4} .4935813{col 71}{space 3} 1.700504
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3937269{col 30}{space 2} .0628079{col 41}{space 1}    6.27{col 50}{space 3}0.000{col 58}{space 4} .2706257{col 71}{space 3} .5168281
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3764184{col 30}{space 2} .0763112{col 41}{space 1}    4.93{col 50}{space 3}0.000{col 58}{space 4} .2268512{col 71}{space 3} .5259856
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4862876{col 30}{space 2} .1334487{col 41}{space 1}    3.64{col 50}{space 3}0.000{col 58}{space 4} .2247329{col 71}{space 3} .7478422
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1323964{col 30}{space 2}  .068775{col 41}{space 1}    1.93{col 50}{space 3}0.054{col 58}{space 4}   -.0024{col 71}{space 3} .2671928
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .2761806{col 30}{space 2} .1445963{col 41}{space 1}    1.91{col 50}{space 3}0.056{col 58}{space 4}-.0072229{col 71}{space 3} .5595842
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2} .0221583{col 30}{space 2} .0075721{col 41}{space 1}    2.93{col 50}{space 3}0.003{col 58}{space 4} .0073173{col 71}{space 3} .0369993
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.2566066{col 30}{space 2} .0331728{col 41}{space 1}   -7.74{col 50}{space 3}0.000{col 58}{space 4} -.321624{col 71}{space 3}-.1915892
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.052668{col 30}{space 2} .1334677{col 41}{space 1}   22.87{col 50}{space 3}0.000{col 58}{space 4} 2.791076{col 71}{space 3} 3.314259
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .67934048
         {txt}sigma_e {c |} {res} 1.0645465
             {txt}rho {c |} {res} .28938692{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,604
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,401

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0425                                         {txt}min = {res}         4
{txt}     between = {res}0.5216                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.3162                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  2198.62
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,401} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .1115004{col 30}{space 2} .0121921{col 41}{space 1}    9.15{col 50}{space 3}0.000{col 58}{space 4} .0876044{col 71}{space 3} .1353964
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0051183{col 30}{space 2} .0110342{col 41}{space 1}    0.46{col 50}{space 3}0.643{col 58}{space 4}-.0165084{col 71}{space 3}  .026745
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1762441{col 30}{space 2} .0907835{col 41}{space 1}   -1.94{col 50}{space 3}0.052{col 58}{space 4}-.3541765{col 71}{space 3} .0016882
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0017121{col 30}{space 2} .0017861{col 41}{space 1}    0.96{col 50}{space 3}0.338{col 58}{space 4}-.0017886{col 71}{space 3} .0052127
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1457013{col 30}{space 2} .0549515{col 41}{space 1}   -2.65{col 50}{space 3}0.008{col 58}{space 4}-.2534043{col 71}{space 3}-.0379983
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2558536{col 30}{space 2} .0552329{col 41}{space 1}    4.63{col 50}{space 3}0.000{col 58}{space 4} .1475991{col 71}{space 3} .3641081
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2063657{col 30}{space 2} .1609303{col 41}{space 1}    1.28{col 50}{space 3}0.200{col 58}{space 4}-.1090518{col 71}{space 3} .5217832
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1364589{col 30}{space 2} .0611699{col 41}{space 1}    2.23{col 50}{space 3}0.026{col 58}{space 4} .0165681{col 71}{space 3} .2563496
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3786448{col 30}{space 2} .1069665{col 41}{space 1}    3.54{col 50}{space 3}0.000{col 58}{space 4} .1689944{col 71}{space 3} .5882952
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1456206{col 30}{space 2}  .065564{col 41}{space 1}    2.22{col 50}{space 3}0.026{col 58}{space 4} .0171176{col 71}{space 3} .2741237
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .272897{col 30}{space 2} .0475002{col 41}{space 1}    5.75{col 50}{space 3}0.000{col 58}{space 4} .1797982{col 71}{space 3} .3659957
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1303056{col 30}{space 2} .0419759{col 41}{space 1}   -3.10{col 50}{space 3}0.002{col 58}{space 4}-.2125769{col 71}{space 3}-.0480342
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0032002{col 30}{space 2} .0315628{col 41}{space 1}   -0.10{col 50}{space 3}0.919{col 58}{space 4}-.0650622{col 71}{space 3} .0586618
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0169954{col 30}{space 2} .0582584{col 41}{space 1}   -0.29{col 50}{space 3}0.770{col 58}{space 4}-.1311798{col 71}{space 3} .0971891
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1239367{col 30}{space 2} .3072852{col 41}{space 1}    0.40{col 50}{space 3}0.687{col 58}{space 4}-.4783311{col 71}{space 3} .7262046
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7511552{col 30}{space 2}  .104703{col 41}{space 1}    7.17{col 50}{space 3}0.000{col 58}{space 4} .5459411{col 71}{space 3} .9563694
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8237114{col 30}{space 2} .1451797{col 41}{space 1}    5.67{col 50}{space 3}0.000{col 58}{space 4} .5391644{col 71}{space 3} 1.108258
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .471678{col 30}{space 2} .1024579{col 41}{space 1}    4.60{col 50}{space 3}0.000{col 58}{space 4} .2708641{col 71}{space 3} .6724919
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3768654{col 30}{space 2} .0974815{col 41}{space 1}    3.87{col 50}{space 3}0.000{col 58}{space 4} .1858051{col 71}{space 3} .5679257
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .7392798{col 30}{space 2} .1793652{col 41}{space 1}    4.12{col 50}{space 3}0.000{col 58}{space 4} .3877305{col 71}{space 3} 1.090829
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0209708{col 30}{space 2} .0178761{col 41}{space 1}   -1.17{col 50}{space 3}0.241{col 58}{space 4}-.0560074{col 71}{space 3} .0140657
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .5545275{col 30}{space 2} .1111028{col 41}{space 1}    4.99{col 50}{space 3}0.000{col 58}{space 4}   .33677{col 71}{space 3} .7722851
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3108061{col 30}{space 2} .0735362{col 41}{space 1}    4.23{col 50}{space 3}0.000{col 58}{space 4} .1666778{col 71}{space 3} .4549344
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.038813{col 30}{space 2} .2475137{col 41}{space 1}   16.32{col 50}{space 3}0.000{col 58}{space 4} 3.553695{col 71}{space 3} 4.523931
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .63753344
         {txt}sigma_e {c |} {res} 1.2853707
             {txt}rho {c |} {res}  .1974369{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,954
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,977

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0484                                         {txt}min = {res}         2
{txt}     between = {res}0.2823                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.2003                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1336.49
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,977} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .1255004{col 30}{space 2} .0185627{col 41}{space 1}    6.76{col 50}{space 3}0.000{col 58}{space 4} .0891182{col 71}{space 3} .1618826
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0029524{col 30}{space 2} .0084265{col 41}{space 1}   -0.35{col 50}{space 3}0.726{col 58}{space 4}-.0194681{col 71}{space 3} .0135633
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.045864{col 30}{space 2} .1078311{col 41}{space 1}   -0.43{col 50}{space 3}0.671{col 58}{space 4}-.2572091{col 71}{space 3}  .165481
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.000585{col 30}{space 2} .0019166{col 41}{space 1}   -0.31{col 50}{space 3}0.760{col 58}{space 4}-.0043416{col 71}{space 3} .0031715
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0912946{col 30}{space 2} .0628559{col 41}{space 1}    1.45{col 50}{space 3}0.146{col 58}{space 4}-.0319008{col 71}{space 3} .2144899
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2878352{col 30}{space 2} .0480997{col 41}{space 1}    5.98{col 50}{space 3}0.000{col 58}{space 4} .1935616{col 71}{space 3} .3821089
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2313346{col 30}{space 2} .0962589{col 41}{space 1}    2.40{col 50}{space 3}0.016{col 58}{space 4} .0426707{col 71}{space 3} .4199985
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1325804{col 30}{space 2}  .075534{col 41}{space 1}    1.76{col 50}{space 3}0.079{col 58}{space 4}-.0154635{col 71}{space 3} .2806242
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2571897{col 30}{space 2} .1084324{col 41}{space 1}    2.37{col 50}{space 3}0.018{col 58}{space 4} .0446661{col 71}{space 3} .4697134
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1962339{col 30}{space 2} .0845613{col 41}{space 1}    2.32{col 50}{space 3}0.020{col 58}{space 4} .0304967{col 71}{space 3} .3619711
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.2184324{col 30}{space 2} .0657614{col 41}{space 1}   -3.32{col 50}{space 3}0.001{col 58}{space 4}-.3473225{col 71}{space 3}-.0895424
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1452852{col 30}{space 2} .0485084{col 41}{space 1}   -3.00{col 50}{space 3}0.003{col 58}{space 4}  -.24036{col 71}{space 3}-.0502104
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0005437{col 30}{space 2} .0019222{col 41}{space 1}    0.28{col 50}{space 3}0.777{col 58}{space 4}-.0032236{col 71}{space 3} .0043111
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0145942{col 30}{space 2} .2386805{col 41}{space 1}    0.06{col 50}{space 3}0.951{col 58}{space 4} -.453211{col 71}{space 3} .4823994
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1640478{col 30}{space 2} .1250739{col 41}{space 1}    1.31{col 50}{space 3}0.190{col 58}{space 4}-.0810926{col 71}{space 3} .4091881
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3911187{col 30}{space 2} .0972684{col 41}{space 1}    4.02{col 50}{space 3}0.000{col 58}{space 4} .2004762{col 71}{space 3} .5817613
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5844471{col 30}{space 2} .1302105{col 41}{space 1}    4.49{col 50}{space 3}0.000{col 58}{space 4} .3292393{col 71}{space 3} .8396549
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2502181{col 30}{space 2} .1108477{col 41}{space 1}    2.26{col 50}{space 3}0.024{col 58}{space 4} .0329605{col 71}{space 3} .4674756
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .5294007{col 30}{space 2} .0855164{col 41}{space 1}    6.19{col 50}{space 3}0.000{col 58}{space 4} .3617915{col 71}{space 3} .6970098
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-1.051197{col 30}{space 2} .3648855{col 41}{space 1}   -2.88{col 50}{space 3}0.004{col 58}{space 4}-1.766359{col 71}{space 3}-.3360345
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.1478104{col 30}{space 2} .0206442{col 41}{space 1}   -7.16{col 50}{space 3}0.000{col 58}{space 4}-.1882724{col 71}{space 3}-.1073484
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .5514908{col 30}{space 2} .1099766{col 41}{space 1}    5.01{col 50}{space 3}0.000{col 58}{space 4} .3359406{col 71}{space 3}  .767041
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.879465{col 30}{space 2} .1818842{col 41}{space 1}   26.83{col 50}{space 3}0.000{col 58}{space 4} 4.522979{col 71}{space 3} 5.235951
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .6147622
         {txt}sigma_e {c |} {res} 1.3643675
             {txt}rho {c |} {res} .16876274{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,812
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,203

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0696                                         {txt}min = {res}         4
{txt}     between = {res}0.4118                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.2591                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1194.21
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,203} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2}-.0150671{col 30}{space 2} .0196649{col 41}{space 1}   -0.77{col 50}{space 3}0.444{col 58}{space 4}-.0536096{col 71}{space 3} .0234754
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}   -.0362{col 30}{space 2} .0125038{col 41}{space 1}   -2.90{col 50}{space 3}0.004{col 58}{space 4} -.060707{col 71}{space 3} -.011693
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .071964{col 30}{space 2}  .096839{col 41}{space 1}    0.74{col 50}{space 3}0.457{col 58}{space 4} -.117837{col 71}{space 3} .2617649
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0024435{col 30}{space 2}  .003212{col 41}{space 1}   -0.76{col 50}{space 3}0.447{col 58}{space 4}-.0087389{col 71}{space 3} .0038519
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0788667{col 30}{space 2} .0690295{col 41}{space 1}    1.14{col 50}{space 3}0.253{col 58}{space 4}-.0564286{col 71}{space 3}  .214162
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0220101{col 30}{space 2} .0507242{col 41}{space 1}    0.43{col 50}{space 3}0.664{col 58}{space 4}-.0774074{col 71}{space 3} .1214276
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0849737{col 30}{space 2} .0655184{col 41}{space 1}    1.30{col 50}{space 3}0.195{col 58}{space 4}-.0434399{col 71}{space 3} .2133874
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2388558{col 30}{space 2} .0664087{col 41}{space 1}    3.60{col 50}{space 3}0.000{col 58}{space 4} .1086971{col 71}{space 3} .3690145
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2541323{col 30}{space 2} .0887354{col 41}{space 1}    2.86{col 50}{space 3}0.004{col 58}{space 4} .0802141{col 71}{space 3} .4280505
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .3039302{col 30}{space 2} .0818692{col 41}{space 1}    3.71{col 50}{space 3}0.000{col 58}{space 4} .1434696{col 71}{space 3} .4643909
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2189019{col 30}{space 2} .0621243{col 41}{space 1}    3.52{col 50}{space 3}0.000{col 58}{space 4} .0971405{col 71}{space 3} .3406633
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0105271{col 30}{space 2}  .089453{col 41}{space 1}   -0.12{col 50}{space 3}0.906{col 58}{space 4}-.1858517{col 71}{space 3} .1647976
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0052435{col 30}{space 2} .0133942{col 41}{space 1}    0.39{col 50}{space 3}0.695{col 58}{space 4}-.0210086{col 71}{space 3} .0314956
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0212429{col 30}{space 2} .1223836{col 41}{space 1}    0.17{col 50}{space 3}0.862{col 58}{space 4}-.2186246{col 71}{space 3} .2611104
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.2353875{col 30}{space 2}  .108546{col 41}{space 1}   -2.17{col 50}{space 3}0.030{col 58}{space 4}-.4481338{col 71}{space 3}-.0226412
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} 1.108538{col 30}{space 2} .1284353{col 41}{space 1}    8.63{col 50}{space 3}0.000{col 58}{space 4} .8568096{col 71}{space 3} 1.360267
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7081908{col 30}{space 2}  .120839{col 41}{space 1}    5.86{col 50}{space 3}0.000{col 58}{space 4} .4713507{col 71}{space 3}  .945031
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1152989{col 30}{space 2} .1284849{col 41}{space 1}    0.90{col 50}{space 3}0.370{col 58}{space 4} -.136527{col 71}{space 3} .3671248
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0494618{col 30}{space 2} .1006787{col 41}{space 1}   -0.49{col 50}{space 3}0.623{col 58}{space 4}-.2467885{col 71}{space 3} .1478649
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-1.215962{col 30}{space 2}  .333053{col 41}{space 1}   -3.65{col 50}{space 3}0.000{col 58}{space 4}-1.868734{col 71}{space 3}-.5631901
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0709739{col 30}{space 2} .0207894{col 41}{space 1}   -3.41{col 50}{space 3}0.001{col 58}{space 4}-.1117203{col 71}{space 3}-.0302275
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5488936{col 30}{space 2} .0621873{col 41}{space 1}   -8.83{col 50}{space 3}0.000{col 58}{space 4}-.6707785{col 71}{space 3}-.4270088
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.3901399{col 30}{space 2} .0614788{col 41}{space 1}   -6.35{col 50}{space 3}0.000{col 58}{space 4}-.5106361{col 71}{space 3}-.2696437
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3345307{col 30}{space 2} .0531052{col 41}{space 1}   -6.30{col 50}{space 3}0.000{col 58}{space 4}-.4386149{col 71}{space 3}-.2304464
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 6.737489{col 30}{space 2} .6404576{col 41}{space 1}   10.52{col 50}{space 3}0.000{col 58}{space 4} 5.482215{col 71}{space 3} 7.992763
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .71880483
         {txt}sigma_e {c |} {res} 1.2513533
             {txt}rho {c |} {res} .24809804{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     1,585
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}       317

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0413                                         {txt}min = {res}         5
{txt}     between = {res}0.4690                                         {txt}avg = {res}       5.0
{txt}     overall = {res}0.2749                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}   370.77
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:317} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2}-.0035527{col 30}{space 2} .0201982{col 41}{space 1}   -0.18{col 50}{space 3}0.860{col 58}{space 4}-.0431405{col 71}{space 3} .0360351
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0821038{col 30}{space 2} .0212191{col 41}{space 1}   -3.87{col 50}{space 3}0.000{col 58}{space 4}-.1236924{col 71}{space 3}-.0405152
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1185365{col 30}{space 2} .1941966{col 41}{space 1}    0.61{col 50}{space 3}0.542{col 58}{space 4}-.2620817{col 71}{space 3} .4991548
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.017912{col 30}{space 2} .0047083{col 41}{space 1}   -3.80{col 50}{space 3}0.000{col 58}{space 4}-.0271401{col 71}{space 3}-.0086838
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2147441{col 30}{space 2} .1187416{col 41}{space 1}    1.81{col 50}{space 3}0.071{col 58}{space 4}-.0179851{col 71}{space 3} .4474733
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0568905{col 30}{space 2} .1208747{col 41}{space 1}    0.47{col 50}{space 3}0.638{col 58}{space 4}-.1800196{col 71}{space 3} .2938006
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2895078{col 30}{space 2} .1436288{col 41}{space 1}    2.02{col 50}{space 3}0.044{col 58}{space 4} .0080006{col 71}{space 3}  .571015
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2177435{col 30}{space 2} .1040965{col 41}{space 1}    2.09{col 50}{space 3}0.036{col 58}{space 4} .0137181{col 71}{space 3} .4217689
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2263692{col 30}{space 2} .1148502{col 41}{space 1}    1.97{col 50}{space 3}0.049{col 58}{space 4}  .001267{col 71}{space 3} .4514714
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1409578{col 30}{space 2} .0794712{col 41}{space 1}    1.77{col 50}{space 3}0.076{col 58}{space 4}-.0148028{col 71}{space 3} .2967184
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .272426{col 30}{space 2} .0905304{col 41}{space 1}    3.01{col 50}{space 3}0.003{col 58}{space 4} .0949896{col 71}{space 3} .4498624
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1685343{col 30}{space 2} .0962373{col 41}{space 1}   -1.75{col 50}{space 3}0.080{col 58}{space 4} -.357156{col 71}{space 3} .0200873
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0072499{col 30}{space 2} .0145847{col 41}{space 1}   -0.50{col 50}{space 3}0.619{col 58}{space 4}-.0358354{col 71}{space 3} .0213356
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.2634026{col 30}{space 2} .1000962{col 41}{space 1}   -2.63{col 50}{space 3}0.009{col 58}{space 4}-.4595876{col 71}{space 3}-.0672176
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1201167{col 30}{space 2} .3045897{col 41}{space 1}    0.39{col 50}{space 3}0.693{col 58}{space 4}-.4768682{col 71}{space 3} .7171016
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  1.07227{col 30}{space 2} .2228425{col 41}{space 1}    4.81{col 50}{space 3}0.000{col 58}{space 4} .6355065{col 71}{space 3} 1.509033
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.327185{col 30}{space 2} .2227485{col 41}{space 1}    5.96{col 50}{space 3}0.000{col 58}{space 4} .8906064{col 71}{space 3} 1.763765
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1718096{col 30}{space 2} .1874807{col 41}{space 1}   -0.92{col 50}{space 3}0.359{col 58}{space 4} -.539265{col 71}{space 3} .1956457
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.1074132{col 30}{space 2} .1993645{col 41}{space 1}   -0.54{col 50}{space 3}0.590{col 58}{space 4}-.4981603{col 71}{space 3}  .283334
{txt}{space 13}imr {c |}{col 18}{res}{space 2} -1.03728{col 30}{space 2} .3448663{col 41}{space 1}   -3.01{col 50}{space 3}0.003{col 58}{space 4}-1.713206{col 71}{space 3}-.3613546
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2} .0458107{col 30}{space 2}  .024287{col 41}{space 1}    1.89{col 50}{space 3}0.059{col 58}{space 4} -.001791{col 71}{space 3} .0934124
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.2060169{col 30}{space 2} .1137316{col 41}{space 1}   -1.81{col 50}{space 3}0.070{col 58}{space 4}-.4289266{col 71}{space 3} .0168929
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0459973{col 30}{space 2} .0860825{col 41}{space 1}    0.53{col 50}{space 3}0.593{col 58}{space 4}-.1227214{col 71}{space 3} .2147159
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0128907{col 30}{space 2} .0888331{col 41}{space 1}    0.15{col 50}{space 3}0.885{col 58}{space 4} -.161219{col 71}{space 3} .1870005
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 7.457881{col 30}{space 2} .9971094{col 41}{space 1}    7.48{col 50}{space 3}0.000{col 58}{space 4} 5.503582{col 71}{space 3} 9.412179
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .68201121
         {txt}sigma_e {c |} {res} 1.2072977
             {txt}rho {c |} {res} .24191896{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. xtreg hdd9  no_species   $xlist  no_species_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,805
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,115

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0754                                         {txt}min = {res}         7
{txt}     between = {res}0.3402                                         {txt}avg = {res}       7.0
{txt}     overall = {res}0.1888                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}  1139.36
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,115} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0210014{col 30}{space 2}  .010518{col 41}{space 1}    2.00{col 50}{space 3}0.046{col 58}{space 4} .0003865{col 71}{space 3} .0416164
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} -.029389{col 30}{space 2} .0096913{col 41}{space 1}   -3.03{col 50}{space 3}0.002{col 58}{space 4}-.0483837{col 71}{space 3}-.0103943
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1503948{col 30}{space 2}  .084945{col 41}{space 1}    1.77{col 50}{space 3}0.077{col 58}{space 4}-.0160943{col 71}{space 3} .3168839
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.006064{col 30}{space 2} .0023901{col 41}{space 1}   -2.54{col 50}{space 3}0.011{col 58}{space 4}-.0107485{col 71}{space 3}-.0013795
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0217505{col 30}{space 2} .0517642{col 41}{space 1}    0.42{col 50}{space 3}0.674{col 58}{space 4}-.0797055{col 71}{space 3} .1232065
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2316494{col 30}{space 2} .0487981{col 41}{space 1}    4.75{col 50}{space 3}0.000{col 58}{space 4} .1360069{col 71}{space 3}  .327292
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1305089{col 30}{space 2} .0666647{col 41}{space 1}    1.96{col 50}{space 3}0.050{col 58}{space 4}-.0001514{col 71}{space 3} .2611693
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3229508{col 30}{space 2} .0488296{col 41}{space 1}    6.61{col 50}{space 3}0.000{col 58}{space 4} .2272465{col 71}{space 3}  .418655
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4409654{col 30}{space 2} .0500607{col 41}{space 1}    8.81{col 50}{space 3}0.000{col 58}{space 4} .3428482{col 71}{space 3} .5390826
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0905263{col 30}{space 2} .0395554{col 41}{space 1}    2.29{col 50}{space 3}0.022{col 58}{space 4} .0129992{col 71}{space 3} .1680534
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1524645{col 30}{space 2} .0410954{col 41}{space 1}    3.71{col 50}{space 3}0.000{col 58}{space 4}  .071919{col 71}{space 3}   .23301
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0159997{col 30}{space 2} .0345755{col 41}{space 1}   -0.46{col 50}{space 3}0.644{col 58}{space 4}-.0837665{col 71}{space 3} .0517671
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0048203{col 30}{space 2} .0016031{col 41}{space 1}    3.01{col 50}{space 3}0.003{col 58}{space 4} .0016784{col 71}{space 3} .0079623
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.1808903{col 30}{space 2} .0456289{col 41}{space 1}   -3.96{col 50}{space 3}0.000{col 58}{space 4}-.2703212{col 71}{space 3}-.0914594
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1887777{col 30}{space 2} .1330727{col 41}{space 1}    1.42{col 50}{space 3}0.156{col 58}{space 4}-.0720401{col 71}{space 3} .4495954
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3592459{col 30}{space 2} .1073361{col 41}{space 1}    3.35{col 50}{space 3}0.001{col 58}{space 4} .1488711{col 71}{space 3} .5696207
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .661557{col 30}{space 2} .1274818{col 41}{space 1}    5.19{col 50}{space 3}0.000{col 58}{space 4} .4116973{col 71}{space 3} .9114167
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1575944{col 30}{space 2} .1004835{col 41}{space 1}    1.57{col 50}{space 3}0.117{col 58}{space 4}-.0393496{col 71}{space 3} .3545385
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3113223{col 30}{space 2} .0892313{col 41}{space 1}    3.49{col 50}{space 3}0.000{col 58}{space 4} .1364321{col 71}{space 3} .4862124
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.8687789{col 30}{space 2} .2101974{col 41}{space 1}   -4.13{col 50}{space 3}0.000{col 58}{space 4}-1.280758{col 71}{space 3}-.4567996
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0064233{col 30}{space 2} .0129999{col 41}{space 1}   -0.49{col 50}{space 3}0.621{col 58}{space 4}-.0319026{col 71}{space 3} .0190561
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.2877904{col 30}{space 2} .0528329{col 41}{space 1}   -5.45{col 50}{space 3}0.000{col 58}{space 4}-.3913411{col 71}{space 3}-.1842398
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.1011077{col 30}{space 2} .0458977{col 41}{space 1}   -2.20{col 50}{space 3}0.028{col 58}{space 4}-.1910656{col 71}{space 3}-.0111497
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .4445649{col 30}{space 2}  .045495{col 41}{space 1}    9.77{col 50}{space 3}0.000{col 58}{space 4} .3553963{col 71}{space 3} .5337335
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1922543{col 30}{space 2} .0470809{col 41}{space 1}    4.08{col 50}{space 3}0.000{col 58}{space 4} .0999774{col 71}{space 3} .2845312
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .4187411{col 30}{space 2} .0451108{col 41}{space 1}    9.28{col 50}{space 3}0.000{col 58}{space 4} .3303255{col 71}{space 3} .5071567
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.481258{col 30}{space 2} .3932299{col 41}{space 1}   13.94{col 50}{space 3}0.000{col 58}{space 4} 4.710542{col 71}{space 3} 6.251975
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}     .6848
         {txt}sigma_e {c |} {res} 1.2390423
             {txt}rho {c |} {res} .23398684{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. 
. esttab using  S11_balance_imr.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(no_species   $xlist  no_species_mean _cons)
{res}{txt}(note: file S11_balance_imr.rtf not found)
(output written to {browse  `"S11_balance_imr.rtf"'})

{com}. 
. 
. 
. 
. 
. 
. ********************************************************************************
. *                                   S12                                        *
. ********************************************************************************
. eststo clear
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist   pdd9_mean i.country i.year, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    35,207
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    10,162

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0401                                         {txt}min = {res}         2
{txt}     between = {res}0.5111                                         {txt}avg = {res}       3.5
{txt}     overall = {res}0.3466                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 13312.15
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:10,162} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}  .071705{col 30}{space 2} .0082167{col 41}{space 1}    8.73{col 50}{space 3}0.000{col 58}{space 4} .0556005{col 71}{space 3} .0878095
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0029738{col 30}{space 2} .0038253{col 41}{space 1}   -0.78{col 50}{space 3}0.437{col 58}{space 4}-.0104713{col 71}{space 3} .0045237
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0079952{col 30}{space 2} .0383408{col 41}{space 1}   -0.21{col 50}{space 3}0.835{col 58}{space 4}-.0831418{col 71}{space 3} .0671513
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0014907{col 30}{space 2} .0007602{col 41}{space 1}   -1.96{col 50}{space 3}0.050{col 58}{space 4}-.0029806{col 71}{space 3}-7.88e-07
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0116788{col 30}{space 2} .0237618{col 41}{space 1}   -0.49{col 50}{space 3}0.623{col 58}{space 4}-.0582511{col 71}{space 3} .0348934
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2464156{col 30}{space 2} .0202656{col 41}{space 1}   12.16{col 50}{space 3}0.000{col 58}{space 4} .2066957{col 71}{space 3} .2861355
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1368403{col 30}{space 2} .0383533{col 41}{space 1}    3.57{col 50}{space 3}0.000{col 58}{space 4} .0616692{col 71}{space 3} .2120114
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1710345{col 30}{space 2}  .024223{col 41}{space 1}    7.06{col 50}{space 3}0.000{col 58}{space 4} .1235583{col 71}{space 3} .2185107
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1896625{col 30}{space 2} .0291051{col 41}{space 1}    6.52{col 50}{space 3}0.000{col 58}{space 4} .1326176{col 71}{space 3} .2467074
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1432683{col 30}{space 2} .0260323{col 41}{space 1}    5.50{col 50}{space 3}0.000{col 58}{space 4} .0922459{col 71}{space 3} .1942908
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1717992{col 30}{space 2} .0223938{col 41}{space 1}    7.67{col 50}{space 3}0.000{col 58}{space 4} .1279082{col 71}{space 3} .2156902
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1042839{col 30}{space 2} .0183649{col 41}{space 1}   -5.68{col 50}{space 3}0.000{col 58}{space 4}-.1402784{col 71}{space 3}-.0682893
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0003416{col 30}{space 2} .0013133{col 41}{space 1}    0.26{col 50}{space 3}0.795{col 58}{space 4}-.0022324{col 71}{space 3} .0029157
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0837971{col 30}{space 2} .0226794{col 41}{space 1}    3.69{col 50}{space 3}0.000{col 58}{space 4} .0393463{col 71}{space 3}  .128248
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0052679{col 30}{space 2} .0594509{col 41}{space 1}    0.09{col 50}{space 3}0.929{col 58}{space 4}-.1112537{col 71}{space 3} .1217896
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5773502{col 30}{space 2} .0397493{col 41}{space 1}   14.52{col 50}{space 3}0.000{col 58}{space 4}  .499443{col 71}{space 3} .6552573
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7463106{col 30}{space 2} .0460711{col 41}{space 1}   16.20{col 50}{space 3}0.000{col 58}{space 4} .6560128{col 71}{space 3} .8366084
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3875032{col 30}{space 2} .0462592{col 41}{space 1}    8.38{col 50}{space 3}0.000{col 58}{space 4} .2968368{col 71}{space 3} .4781697
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2132751{col 30}{space 2} .0361728{col 41}{space 1}    5.90{col 50}{space 3}0.000{col 58}{space 4} .1423776{col 71}{space 3} .2841725
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.1722808{col 30}{space 2} .0693207{col 41}{space 1}   -2.49{col 50}{space 3}0.013{col 58}{space 4}-.3081468{col 71}{space 3}-.0364147
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0075372{col 30}{space 2} .0107962{col 41}{space 1}    0.70{col 50}{space 3}0.485{col 58}{space 4}-.0136228{col 71}{space 3} .0286973
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.2540979{col 30}{space 2} .0724269{col 41}{space 1}   -3.51{col 50}{space 3}0.000{col 58}{space 4} -.396052{col 71}{space 3}-.1121438
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.466123{col 30}{space 2} .0399836{col 41}{space 1}  -36.67{col 50}{space 3}0.000{col 58}{space 4}-1.544489{col 71}{space 3}-1.387756
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.3982412{col 30}{space 2} .0584442{col 41}{space 1}   -6.81{col 50}{space 3}0.000{col 58}{space 4}-.5127897{col 71}{space 3}-.2836927
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2} -.017569{col 30}{space 2} .1265746{col 41}{space 1}   -0.14{col 50}{space 3}0.890{col 58}{space 4}-.2656507{col 71}{space 3} .2305127
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .4957357{col 30}{space 2} .0462146{col 41}{space 1}   10.73{col 50}{space 3}0.000{col 58}{space 4} .4051567{col 71}{space 3} .5863147
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.1575624{col 30}{space 2} .0906615{col 41}{space 1}   -1.74{col 50}{space 3}0.082{col 58}{space 4}-.3352557{col 71}{space 3} .0201309
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0362764{col 30}{space 2} .0810468{col 41}{space 1}   -0.45{col 50}{space 3}0.654{col 58}{space 4}-.1951252{col 71}{space 3} .1225724
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .1196019{col 30}{space 2} .0825076{col 41}{space 1}    1.45{col 50}{space 3}0.147{col 58}{space 4}  -.04211{col 71}{space 3} .2813139
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .1001532{col 30}{space 2} .0837904{col 41}{space 1}    1.20{col 50}{space 3}0.232{col 58}{space 4}-.0640729{col 71}{space 3} .2643793
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1411467{col 30}{space 2} .0843921{col 41}{space 1}    1.67{col 50}{space 3}0.094{col 58}{space 4}-.0242588{col 71}{space 3} .3065522
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.1315434{col 30}{space 2} .0856995{col 41}{space 1}   -1.53{col 50}{space 3}0.125{col 58}{space 4}-.2995113{col 71}{space 3} .0364245
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .2743944{col 30}{space 2} .0841145{col 41}{space 1}    3.26{col 50}{space 3}0.001{col 58}{space 4}  .109533{col 71}{space 3} .4392558
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.0635846{col 30}{space 2} .0944808{col 41}{space 1}   -0.67{col 50}{space 3}0.501{col 58}{space 4}-.2487636{col 71}{space 3} .1215943
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .5521723{col 30}{space 2} .0864709{col 41}{space 1}    6.39{col 50}{space 3}0.000{col 58}{space 4} .3826924{col 71}{space 3} .7216522
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .2064655{col 30}{space 2} .0885958{col 41}{space 1}    2.33{col 50}{space 3}0.020{col 58}{space 4} .0328209{col 71}{space 3} .3801101
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.571524{col 30}{space 2} .1101966{col 41}{space 1}   41.49{col 50}{space 3}0.000{col 58}{space 4} 4.355543{col 71}{space 3} 4.787506
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .70265628
         {txt}sigma_e {c |} {res} 1.2295519
             {txt}rho {c |} {res} .24618301{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,447
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,149

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0298                                         {txt}min = {res}         3
{txt}     between = {res}0.3080                                         {txt}avg = {res}       3.0
{txt}     overall = {res}0.1978                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1608.51
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,149} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0926364{col 30}{space 2} .0121316{col 41}{space 1}    7.64{col 50}{space 3}0.000{col 58}{space 4}  .068859{col 71}{space 3} .1164138
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0509557{col 30}{space 2} .0083905{col 41}{space 1}    6.07{col 50}{space 3}0.000{col 58}{space 4} .0345107{col 71}{space 3} .0674007
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0115983{col 30}{space 2} .0643923{col 41}{space 1}   -0.18{col 50}{space 3}0.857{col 58}{space 4}-.1378048{col 71}{space 3} .1146082
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}  .001096{col 30}{space 2} .0012387{col 41}{space 1}    0.88{col 50}{space 3}0.376{col 58}{space 4}-.0013318{col 71}{space 3} .0035237
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0160855{col 30}{space 2} .0410196{col 41}{space 1}    0.39{col 50}{space 3}0.695{col 58}{space 4}-.0643115{col 71}{space 3} .0964825
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3154329{col 30}{space 2} .0332007{col 41}{space 1}    9.50{col 50}{space 3}0.000{col 58}{space 4} .2503607{col 71}{space 3}  .380505
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.1669504{col 30}{space 2} .1576197{col 41}{space 1}   -1.06{col 50}{space 3}0.290{col 58}{space 4}-.4758794{col 71}{space 3} .1419785
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1120245{col 30}{space 2}  .040854{col 41}{space 1}    2.74{col 50}{space 3}0.006{col 58}{space 4} .0319522{col 71}{space 3} .1920969
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0397141{col 30}{space 2} .0519249{col 41}{space 1}   -0.76{col 50}{space 3}0.444{col 58}{space 4}-.1414851{col 71}{space 3} .0620568
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0416844{col 30}{space 2} .0712799{col 41}{space 1}    0.58{col 50}{space 3}0.559{col 58}{space 4}-.0980215{col 71}{space 3} .1813904
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2467322{col 30}{space 2} .0512839{col 41}{space 1}    4.81{col 50}{space 3}0.000{col 58}{space 4} .1462175{col 71}{space 3} .3472468
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1678291{col 30}{space 2}   .03133{col 41}{space 1}   -5.36{col 50}{space 3}0.000{col 58}{space 4}-.2292347{col 71}{space 3}-.1064234
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0064576{col 30}{space 2} .0036387{col 41}{space 1}    1.77{col 50}{space 3}0.076{col 58}{space 4} -.000674{col 71}{space 3} .0135892
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2976618{col 30}{space 2} .0338425{col 41}{space 1}    8.80{col 50}{space 3}0.000{col 58}{space 4} .2313317{col 71}{space 3} .3639919
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} 1.111856{col 30}{space 2}  .310295{col 41}{space 1}    3.58{col 50}{space 3}0.000{col 58}{space 4} .5036895{col 71}{space 3} 1.720023
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4353143{col 30}{space 2} .0623525{col 41}{space 1}    6.98{col 50}{space 3}0.000{col 58}{space 4} .3131055{col 71}{space 3}  .557523
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .498777{col 30}{space 2} .0764719{col 41}{space 1}    6.52{col 50}{space 3}0.000{col 58}{space 4} .3488948{col 71}{space 3} .6486592
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .5182029{col 30}{space 2} .1340146{col 41}{space 1}    3.87{col 50}{space 3}0.000{col 58}{space 4} .2555392{col 71}{space 3} .7808667
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .114883{col 30}{space 2} .0684131{col 41}{space 1}    1.68{col 50}{space 3}0.093{col 58}{space 4}-.0192042{col 71}{space 3} .2489701
{txt}{space 13}imr {c |}{col 18}{res}{space 2} 1.215181{col 30}{space 2} .1692729{col 41}{space 1}    7.18{col 50}{space 3}0.000{col 58}{space 4} .8834125{col 71}{space 3}  1.54695
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .1028263{col 30}{space 2} .0165984{col 41}{space 1}    6.19{col 50}{space 3}0.000{col 58}{space 4} .0702941{col 71}{space 3} .1353585
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.4053915{col 30}{space 2}  .035636{col 41}{space 1}  -11.38{col 50}{space 3}0.000{col 58}{space 4}-.4752368{col 71}{space 3}-.3355462
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.121754{col 30}{space 2} .1565614{col 41}{space 1}   13.55{col 50}{space 3}0.000{col 58}{space 4} 1.814899{col 71}{space 3} 2.428609
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .66759032
         {txt}sigma_e {c |} {res} 1.0626719
             {txt}rho {c |} {res}  .2829787{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,604
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,401

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0421                                         {txt}min = {res}         4
{txt}     between = {res}0.5191                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.3146                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  2180.66
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,401} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1658523{col 30}{space 2} .0185635{col 41}{space 1}    8.93{col 50}{space 3}0.000{col 58}{space 4} .1294685{col 71}{space 3} .2022361
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0082525{col 30}{space 2} .0110428{col 41}{space 1}    0.75{col 50}{space 3}0.455{col 58}{space 4} -.013391{col 71}{space 3} .0298961
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1743581{col 30}{space 2} .0910019{col 41}{space 1}   -1.92{col 50}{space 3}0.055{col 58}{space 4}-.3527186{col 71}{space 3} .0040024
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0028045{col 30}{space 2} .0018212{col 41}{space 1}    1.54{col 50}{space 3}0.124{col 58}{space 4}-.0007649{col 71}{space 3}  .006374
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1519025{col 30}{space 2} .0550036{col 41}{space 1}   -2.76{col 50}{space 3}0.006{col 58}{space 4}-.2597075{col 71}{space 3}-.0440975
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .253936{col 30}{space 2} .0552539{col 41}{space 1}    4.60{col 50}{space 3}0.000{col 58}{space 4} .1456404{col 71}{space 3} .3622316
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2261296{col 30}{space 2} .1618473{col 41}{space 1}    1.40{col 50}{space 3}0.162{col 58}{space 4}-.0910852{col 71}{space 3} .5433444
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1285621{col 30}{space 2} .0614811{col 41}{space 1}    2.09{col 50}{space 3}0.037{col 58}{space 4} .0080614{col 71}{space 3} .2490628
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3559814{col 30}{space 2} .1069679{col 41}{space 1}    3.33{col 50}{space 3}0.001{col 58}{space 4}  .146328{col 71}{space 3} .5656347
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1413688{col 30}{space 2} .0655707{col 41}{space 1}    2.16{col 50}{space 3}0.031{col 58}{space 4} .0128526{col 71}{space 3} .2698851
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2715333{col 30}{space 2} .0475652{col 41}{space 1}    5.71{col 50}{space 3}0.000{col 58}{space 4} .1783071{col 71}{space 3} .3647594
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1193979{col 30}{space 2} .0423286{col 41}{space 1}   -2.82{col 50}{space 3}0.005{col 58}{space 4}-.2023605{col 71}{space 3}-.0364354
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0093658{col 30}{space 2} .0318221{col 41}{space 1}    0.29{col 50}{space 3}0.769{col 58}{space 4}-.0530045{col 71}{space 3}  .071736
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1244686{col 30}{space 2} .0582879{col 41}{space 1}    2.14{col 50}{space 3}0.033{col 58}{space 4} .0102264{col 71}{space 3} .2387108
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .134553{col 30}{space 2} .3047645{col 41}{space 1}    0.44{col 50}{space 3}0.659{col 58}{space 4}-.4627744{col 71}{space 3} .7318804
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7353138{col 30}{space 2} .1049748{col 41}{space 1}    7.00{col 50}{space 3}0.000{col 58}{space 4}  .529567{col 71}{space 3} .9410606
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8555538{col 30}{space 2} .1464566{col 41}{space 1}    5.84{col 50}{space 3}0.000{col 58}{space 4} .5685042{col 71}{space 3} 1.142603
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4714976{col 30}{space 2} .1023921{col 41}{space 1}    4.60{col 50}{space 3}0.000{col 58}{space 4} .2708129{col 71}{space 3} .6721824
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3924118{col 30}{space 2} .0974439{col 41}{space 1}    4.03{col 50}{space 3}0.000{col 58}{space 4} .2014251{col 71}{space 3} .5833984
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .9377826{col 30}{space 2} .1946119{col 41}{space 1}    4.82{col 50}{space 3}0.000{col 58}{space 4} .5563504{col 71}{space 3} 1.319215
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0301229{col 30}{space 2}  .028003{col 41}{space 1}   -1.08{col 50}{space 3}0.282{col 58}{space 4}-.0850078{col 71}{space 3} .0247619
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .6663323{col 30}{space 2} .1191091{col 41}{space 1}    5.59{col 50}{space 3}0.000{col 58}{space 4} .4328828{col 71}{space 3} .8997818
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3980054{col 30}{space 2} .0787964{col 41}{space 1}    5.05{col 50}{space 3}0.000{col 58}{space 4} .2435673{col 71}{space 3} .5524435
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.749473{col 30}{space 2} .2734491{col 41}{space 1}   13.71{col 50}{space 3}0.000{col 58}{space 4} 3.213523{col 71}{space 3} 4.285424
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .63998185
         {txt}sigma_e {c |} {res} 1.2854624
             {txt}rho {c |} {res} .19863175{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,954
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,977

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0428                                         {txt}min = {res}         2
{txt}     between = {res}0.2817                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.1980                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1329.05
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,977} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2104724{col 30}{space 2} .0381953{col 41}{space 1}    5.51{col 50}{space 3}0.000{col 58}{space 4}  .135611{col 71}{space 3} .2853338
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0026953{col 30}{space 2} .0085864{col 41}{space 1}   -0.31{col 50}{space 3}0.754{col 58}{space 4}-.0195242{col 71}{space 3} .0141337
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0358775{col 30}{space 2} .1078424{col 41}{space 1}   -0.33{col 50}{space 3}0.739{col 58}{space 4}-.2472446{col 71}{space 3} .1754897
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0002936{col 30}{space 2} .0020301{col 41}{space 1}   -0.14{col 50}{space 3}0.885{col 58}{space 4}-.0042726{col 71}{space 3} .0036854
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0973553{col 30}{space 2} .0625918{col 41}{space 1}    1.56{col 50}{space 3}0.120{col 58}{space 4}-.0253225{col 71}{space 3}  .220033
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2948195{col 30}{space 2} .0480022{col 41}{space 1}    6.14{col 50}{space 3}0.000{col 58}{space 4} .2007368{col 71}{space 3} .3889021
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2320101{col 30}{space 2} .0960306{col 41}{space 1}    2.42{col 50}{space 3}0.016{col 58}{space 4} .0437936{col 71}{space 3} .4202266
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1374811{col 30}{space 2} .0758321{col 41}{space 1}    1.81{col 50}{space 3}0.070{col 58}{space 4}-.0111471{col 71}{space 3} .2861092
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2687401{col 30}{space 2} .1075554{col 41}{space 1}    2.50{col 50}{space 3}0.012{col 58}{space 4} .0579353{col 71}{space 3} .4795449
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2134285{col 30}{space 2}  .083713{col 41}{space 1}    2.55{col 50}{space 3}0.011{col 58}{space 4}  .049354{col 71}{space 3} .3775029
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1976476{col 30}{space 2} .0661066{col 41}{space 1}   -2.99{col 50}{space 3}0.003{col 58}{space 4}-.3272142{col 71}{space 3}-.0680811
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.139152{col 30}{space 2} .0485427{col 41}{space 1}   -2.87{col 50}{space 3}0.004{col 58}{space 4} -.234294{col 71}{space 3}  -.04401
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0005291{col 30}{space 2} .0019347{col 41}{space 1}    0.27{col 50}{space 3}0.784{col 58}{space 4}-.0032628{col 71}{space 3}  .004321
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0769775{col 30}{space 2} .2369487{col 41}{space 1}    0.32{col 50}{space 3}0.745{col 58}{space 4}-.3874335{col 71}{space 3} .5413884
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1637518{col 30}{space 2} .1251955{col 41}{space 1}    1.31{col 50}{space 3}0.191{col 58}{space 4}-.0816269{col 71}{space 3} .4091305
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .387291{col 30}{space 2} .0974557{col 41}{space 1}    3.97{col 50}{space 3}0.000{col 58}{space 4} .1962814{col 71}{space 3} .5783006
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5749522{col 30}{space 2} .1295902{col 41}{space 1}    4.44{col 50}{space 3}0.000{col 58}{space 4} .3209601{col 71}{space 3} .8289444
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2371614{col 30}{space 2} .1102117{col 41}{space 1}    2.15{col 50}{space 3}0.031{col 58}{space 4} .0211504{col 71}{space 3} .4531723
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .5138407{col 30}{space 2} .0856784{col 41}{space 1}    6.00{col 50}{space 3}0.000{col 58}{space 4}  .345914{col 71}{space 3} .6817673
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.9359549{col 30}{space 2} .4055045{col 41}{space 1}   -2.31{col 50}{space 3}0.021{col 58}{space 4}-1.730729{col 71}{space 3}-.1411807
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2419996{col 30}{space 2} .0405499{col 41}{space 1}   -5.97{col 50}{space 3}0.000{col 58}{space 4}-.3214759{col 71}{space 3}-.1625232
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .5349687{col 30}{space 2} .1200784{col 41}{space 1}    4.46{col 50}{space 3}0.000{col 58}{space 4} .2996194{col 71}{space 3}  .770318
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.812285{col 30}{space 2} .2060243{col 41}{space 1}   23.36{col 50}{space 3}0.000{col 58}{space 4} 4.408485{col 71}{space 3} 5.216085
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .60993882
         {txt}sigma_e {c |} {res} 1.3686364
             {txt}rho {c |} {res} .16569875{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,812
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,203

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0700                                         {txt}min = {res}         4
{txt}     between = {res}0.4045                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.2553                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1152.39
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,203} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .3118177{col 30}{space 2} .1793998{col 41}{space 1}    1.74{col 50}{space 3}0.082{col 58}{space 4}-.0397994{col 71}{space 3} .6634348
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0681402{col 30}{space 2}  .055454{col 41}{space 1}    1.23{col 50}{space 3}0.219{col 58}{space 4}-.0405477{col 71}{space 3} .1768281
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0943283{col 30}{space 2} .0974466{col 41}{space 1}    0.97{col 50}{space 3}0.333{col 58}{space 4}-.0966635{col 71}{space 3} .2853201
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0248901{col 30}{space 2} .0139569{col 41}{space 1}    1.78{col 50}{space 3}0.075{col 58}{space 4}-.0024649{col 71}{space 3} .0522452
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0715875{col 30}{space 2} .0694866{col 41}{space 1}    1.03{col 50}{space 3}0.303{col 58}{space 4}-.0646038{col 71}{space 3} .2077788
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0851301{col 30}{space 2} .0586122{col 41}{space 1}    1.45{col 50}{space 3}0.146{col 58}{space 4}-.0297477{col 71}{space 3} .2000078
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1533123{col 30}{space 2} .0741848{col 41}{space 1}    2.07{col 50}{space 3}0.039{col 58}{space 4} .0079127{col 71}{space 3} .2987119
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0467813{col 30}{space 2} .1181464{col 41}{space 1}    0.40{col 50}{space 3}0.692{col 58}{space 4}-.1847814{col 71}{space 3} .2783439
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.1545311{col 30}{space 2} .2224088{col 41}{space 1}   -0.69{col 50}{space 3}0.487{col 58}{space 4}-.5904442{col 71}{space 3} .2813821
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2243294{col 30}{space 2} .0911624{col 41}{space 1}    2.46{col 50}{space 3}0.014{col 58}{space 4} .0456544{col 71}{space 3} .4030045
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3472016{col 30}{space 2} .0855553{col 41}{space 1}    4.06{col 50}{space 3}0.000{col 58}{space 4} .1795163{col 71}{space 3} .5148869
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0643603{col 30}{space 2} .0973823{col 41}{space 1}    0.66{col 50}{space 3}0.509{col 58}{space 4}-.1265055{col 71}{space 3} .2552262
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0152774{col 30}{space 2} .0150914{col 41}{space 1}   -1.01{col 50}{space 3}0.311{col 58}{space 4} -.044856{col 71}{space 3} .0143013
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .4929554{col 30}{space 2} .2898538{col 41}{space 1}    1.70{col 50}{space 3}0.089{col 58}{space 4}-.0751475{col 71}{space 3} 1.061058
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.2542823{col 30}{space 2}  .108957{col 41}{space 1}   -2.33{col 50}{space 3}0.020{col 58}{space 4}-.4678341{col 71}{space 3}-.0407304
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} 1.134777{col 30}{space 2}  .129298{col 41}{space 1}    8.78{col 50}{space 3}0.000{col 58}{space 4} .8813578{col 71}{space 3} 1.388196
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7930821{col 30}{space 2} .1207242{col 41}{space 1}    6.57{col 50}{space 3}0.000{col 58}{space 4} .5564671{col 71}{space 3} 1.029697
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1449366{col 30}{space 2} .1302491{col 41}{space 1}    1.11{col 50}{space 3}0.266{col 58}{space 4} -.110347{col 71}{space 3} .4002203
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0688356{col 30}{space 2} .1020254{col 41}{space 1}   -0.67{col 50}{space 3}0.500{col 58}{space 4}-.2688018{col 71}{space 3} .1311306
{txt}{space 13}imr {c |}{col 18}{res}{space 2} 2.461138{col 30}{space 2} 1.866956{col 41}{space 1}    1.32{col 50}{space 3}0.187{col 58}{space 4}-1.198029{col 71}{space 3} 6.120305
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0488306{col 30}{space 2} .0384821{col 41}{space 1}   -1.27{col 50}{space 3}0.204{col 58}{space 4}-.1242541{col 71}{space 3} .0265928
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.7900939{col 30}{space 2} .1292549{col 41}{space 1}   -6.11{col 50}{space 3}0.000{col 58}{space 4}-1.043429{col 71}{space 3} -.536759
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.6307311{col 30}{space 2} .1317246{col 41}{space 1}   -4.79{col 50}{space 3}0.000{col 58}{space 4}-.8889065{col 71}{space 3}-.3725557
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3975054{col 30}{space 2} .0577778{col 41}{space 1}   -6.88{col 50}{space 3}0.000{col 58}{space 4}-.5107478{col 71}{space 3}-.2842631
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.3991803{col 30}{space 2} 3.559331{col 41}{space 1}   -0.11{col 50}{space 3}0.911{col 58}{space 4} -7.37534{col 71}{space 3} 6.576979
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .7267327
         {txt}sigma_e {c |} {res} 1.2509612
             {txt}rho {c |} {res} .25233121{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     1,585
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}       317

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0447                                         {txt}min = {res}         5
{txt}     between = {res}0.4616                                         {txt}avg = {res}       5.0
{txt}     overall = {res}0.2724                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}   371.95
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:317} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .6764453{col 30}{space 2}  .482425{col 41}{space 1}    1.40{col 50}{space 3}0.161{col 58}{space 4}-.2690903{col 71}{space 3} 1.621981
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .1070948{col 30}{space 2} .1531494{col 41}{space 1}    0.70{col 50}{space 3}0.484{col 58}{space 4}-.1930726{col 71}{space 3} .4072621
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1475157{col 30}{space 2} .1942788{col 41}{space 1}    0.76{col 50}{space 3}0.448{col 58}{space 4}-.2332637{col 71}{space 3} .5282952
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0302035{col 30}{space 2} .0365945{col 41}{space 1}    0.83{col 50}{space 3}0.409{col 58}{space 4}-.0415203{col 71}{space 3} .1019274
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1893215{col 30}{space 2} .1218016{col 41}{space 1}    1.55{col 50}{space 3}0.120{col 58}{space 4}-.0494053{col 71}{space 3} .4280482
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1859048{col 30}{space 2} .1496807{col 41}{space 1}    1.24{col 50}{space 3}0.214{col 58}{space 4} -.107464{col 71}{space 3} .4792735
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .4142419{col 30}{space 2} .1756511{col 41}{space 1}    2.36{col 50}{space 3}0.018{col 58}{space 4} .0699721{col 71}{space 3} .7585116
{txt}{space 11}phone {c |}{col 18}{res}{space 2}-.1444968{col 30}{space 2} .2951534{col 41}{space 1}   -0.49{col 50}{space 3}0.624{col 58}{space 4}-.7229868{col 71}{space 3} .4339931
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.4782641{col 30}{space 2} .5517455{col 41}{space 1}   -0.87{col 50}{space 3}0.386{col 58}{space 4}-1.559665{col 71}{space 3} .6031373
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0006579{col 30}{space 2} .1305997{col 41}{space 1}   -0.01{col 50}{space 3}0.996{col 58}{space 4}-.2566286{col 71}{space 3} .2553128
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .4799207{col 30}{space 2} .1890655{col 41}{space 1}    2.54{col 50}{space 3}0.011{col 58}{space 4} .1093591{col 71}{space 3} .8504823
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.026683{col 30}{space 2} .1465401{col 41}{space 1}   -0.18{col 50}{space 3}0.856{col 58}{space 4}-.3138963{col 71}{space 3} .2605303
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0301006{col 30}{space 2} .0257774{col 41}{space 1}   -1.17{col 50}{space 3}0.243{col 58}{space 4}-.0806232{col 71}{space 3} .0204221
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .7239003{col 30}{space 2} .7316867{col 41}{space 1}    0.99{col 50}{space 3}0.322{col 58}{space 4}-.7101792{col 71}{space 3}  2.15798
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .238948{col 30}{space 2} .3189756{col 41}{space 1}    0.75{col 50}{space 3}0.454{col 58}{space 4}-.3862328{col 71}{space 3} .8641287
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} 1.108172{col 30}{space 2}   .22445{col 41}{space 1}    4.94{col 50}{space 3}0.000{col 58}{space 4} .6682583{col 71}{space 3} 1.548086
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.160568{col 30}{space 2} .2251404{col 41}{space 1}    5.15{col 50}{space 3}0.000{col 58}{space 4} .7193006{col 71}{space 3} 1.601835
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1969852{col 30}{space 2} .1872703{col 41}{space 1}   -1.05{col 50}{space 3}0.293{col 58}{space 4}-.5640283{col 71}{space 3} .1700579
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.1687735{col 30}{space 2} .1989155{col 41}{space 1}   -0.85{col 50}{space 3}0.396{col 58}{space 4}-.5586407{col 71}{space 3} .2210937
{txt}{space 13}imr {c |}{col 18}{res}{space 2} 4.712536{col 30}{space 2}  4.44151{col 41}{space 1}    1.06{col 50}{space 3}0.289{col 58}{space 4}-3.992664{col 71}{space 3} 13.41774
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0565192{col 30}{space 2}  .051824{col 41}{space 1}   -1.09{col 50}{space 3}0.275{col 58}{space 4}-.1580924{col 71}{space 3} .0450541
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .5299155{col 30}{space 2} .5737749{col 41}{space 1}    0.92{col 50}{space 3}0.356{col 58}{space 4}-.5946626{col 71}{space 3} 1.654494
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.2914898{col 30}{space 2} .2761826{col 41}{space 1}   -1.06{col 50}{space 3}0.291{col 58}{space 4}-.8327978{col 71}{space 3} .2498182
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .6058986{col 30}{space 2} .4596036{col 41}{space 1}    1.32{col 50}{space 3}0.187{col 58}{space 4} -.294908{col 71}{space 3} 1.506705
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-8.478747{col 30}{space 2} 12.50376{col 41}{space 1}   -0.68{col 50}{space 3}0.498{col 58}{space 4}-32.98567{col 71}{space 3} 16.02818
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .71738604
         {txt}sigma_e {c |} {res} 1.2084218
             {txt}rho {c |} {res} .26058837{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,805
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,115

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0776                                         {txt}min = {res}         7
{txt}     between = {res}0.3320                                         {txt}avg = {res}       7.0
{txt}     overall = {res}0.1866                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}  1115.43
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,115} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}-.1533823{col 30}{space 2} .0717621{col 41}{space 1}   -2.14{col 50}{space 3}0.033{col 58}{space 4}-.2940333{col 71}{space 3}-.0127312
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0787488{col 30}{space 2}  .022608{col 41}{space 1}   -3.48{col 50}{space 3}0.000{col 58}{space 4}-.1230596{col 71}{space 3} -.034438
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1402673{col 30}{space 2} .0853401{col 41}{space 1}    1.64{col 50}{space 3}0.100{col 58}{space 4}-.0269962{col 71}{space 3} .3075307
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0197903{col 30}{space 2} .0059951{col 41}{space 1}   -3.30{col 50}{space 3}0.001{col 58}{space 4}-.0315405{col 71}{space 3}-.0080401
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0223929{col 30}{space 2} .0519247{col 41}{space 1}    0.43{col 50}{space 3}0.666{col 58}{space 4}-.0793777{col 71}{space 3} .1241634
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2035195{col 30}{space 2} .0514123{col 41}{space 1}    3.96{col 50}{space 3}0.000{col 58}{space 4} .1027533{col 71}{space 3} .3042857
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0928686{col 30}{space 2} .0682192{col 41}{space 1}    1.36{col 50}{space 3}0.173{col 58}{space 4}-.0408385{col 71}{space 3} .2265757
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3965191{col 30}{space 2}    .0583{col 41}{space 1}    6.80{col 50}{space 3}0.000{col 58}{space 4} .2822533{col 71}{space 3} .5107849
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .5888886{col 30}{space 2} .0789515{col 41}{space 1}    7.46{col 50}{space 3}0.000{col 58}{space 4} .4341464{col 71}{space 3} .7436307
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1327161{col 30}{space 2} .0427448{col 41}{space 1}    3.10{col 50}{space 3}0.002{col 58}{space 4} .0489378{col 71}{space 3} .2164944
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1110383{col 30}{space 2} .0444668{col 41}{space 1}    2.50{col 50}{space 3}0.013{col 58}{space 4} .0238849{col 71}{space 3} .1981917
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0404663{col 30}{space 2} .0363351{col 41}{space 1}   -1.11{col 50}{space 3}0.265{col 58}{space 4}-.1116817{col 71}{space 3} .0307492
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0132976{col 30}{space 2} .0036275{col 41}{space 1}    3.67{col 50}{space 3}0.000{col 58}{space 4} .0061879{col 71}{space 3} .0204073
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.4044506{col 30}{space 2} .1110153{col 41}{space 1}   -3.64{col 50}{space 3}0.000{col 58}{space 4}-.6220366{col 71}{space 3}-.1868646
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1799691{col 30}{space 2} .1347182{col 41}{space 1}    1.34{col 50}{space 3}0.182{col 58}{space 4}-.0840737{col 71}{space 3}  .444012
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3731791{col 30}{space 2} .1076912{col 41}{space 1}    3.47{col 50}{space 3}0.001{col 58}{space 4} .1621083{col 71}{space 3} .5842499
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7389758{col 30}{space 2} .1328967{col 41}{space 1}    5.56{col 50}{space 3}0.000{col 58}{space 4} .4785031{col 71}{space 3} .9994486
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .149865{col 30}{space 2} .1007811{col 41}{space 1}    1.49{col 50}{space 3}0.137{col 58}{space 4}-.0476623{col 71}{space 3} .3473922
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2891402{col 30}{space 2} .0904729{col 41}{space 1}    3.20{col 50}{space 3}0.001{col 58}{space 4} .1118166{col 71}{space 3} .4664638
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-2.817831{col 30}{space 2} .8084505{col 41}{space 1}   -3.49{col 50}{space 3}0.000{col 58}{space 4}-4.402365{col 71}{space 3}-1.233297
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0026485{col 30}{space 2}  .026041{col 41}{space 1}   -0.10{col 50}{space 3}0.919{col 58}{space 4} -.053688{col 71}{space 3} .0483909
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.4927605{col 30}{space 2} .1037751{col 41}{space 1}   -4.75{col 50}{space 3}0.000{col 58}{space 4}-.6961559{col 71}{space 3} -.289365
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0742764{col 30}{space 2} .0462549{col 41}{space 1}   -1.61{col 50}{space 3}0.108{col 58}{space 4}-.1649344{col 71}{space 3} .0163816
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .5185085{col 30}{space 2}  .057404{col 41}{space 1}    9.03{col 50}{space 3}0.000{col 58}{space 4} .4059988{col 71}{space 3} .6310182
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .3199417{col 30}{space 2}  .070131{col 41}{space 1}    4.56{col 50}{space 3}0.000{col 58}{space 4} .1824875{col 71}{space 3}  .457396
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .4684192{col 30}{space 2} .0529006{col 41}{space 1}    8.85{col 50}{space 3}0.000{col 58}{space 4} .3647359{col 71}{space 3} .5721024
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 8.892818{col 30}{space 2} 1.430517{col 41}{space 1}    6.22{col 50}{space 3}0.000{col 58}{space 4} 6.089057{col 71}{space 3} 11.69658
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .66654359
         {txt}sigma_e {c |} {res} 1.2369395
             {txt}rho {c |} {res} .22503187{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S12_balance_imr.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean _cons)
{res}{txt}(note: file S12_balance_imr.rtf not found)
(output written to {browse  `"S12_balance_imr.rtf"'})

{com}. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. ******************************************************************************** 
. *                                  S13_S14                                     *
. ********************************************************************************
. preserve
{txt}
{com}. eststo clear
{txt}
{com}. drop if hdd9_own==.|hdd9_purchase==.
{txt}(2,055 observations deleted)

{com}. drop  pdd9_mean no_species_mean hhsize_mean dependent_share_mean head_age_mean female_head_mean head_read_mean motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean weather_shock_mean plot_area_mean other_crop_mean
{txt}
{com}. foreach x of varlist pdd9 hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. 
. eststo clear
{txt}
{com}. xtreg hdd9_own  pdd9   $xlist  pdd9_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    33,152
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    10,109

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0815                                         {txt}min = {res}         1
{txt}     between = {res}0.6270                                         {txt}avg = {res}       3.3
{txt}     overall = {res}0.4813                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 24612.04
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:10,109} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1510122{col 30}{space 2} .0082158{col 41}{space 1}   18.38{col 50}{space 3}0.000{col 58}{space 4} .1349095{col 71}{space 3} .1671149
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0063189{col 30}{space 2} .0030282{col 41}{space 1}   -2.09{col 50}{space 3}0.037{col 58}{space 4}-.0122541{col 71}{space 3}-.0003838
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0222447{col 30}{space 2} .0310975{col 41}{space 1}   -0.72{col 50}{space 3}0.474{col 58}{space 4}-.0831948{col 71}{space 3} .0387053
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0026658{col 30}{space 2} .0005963{col 41}{space 1}   -4.47{col 50}{space 3}0.000{col 58}{space 4}-.0038345{col 71}{space 3} -.001497
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0743524{col 30}{space 2} .0193666{col 41}{space 1}   -3.84{col 50}{space 3}0.000{col 58}{space 4}-.1123103{col 71}{space 3}-.0363945
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0764321{col 30}{space 2} .0165484{col 41}{space 1}    4.62{col 50}{space 3}0.000{col 58}{space 4} .0439978{col 71}{space 3} .1088664
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0182369{col 30}{space 2} .0302327{col 41}{space 1}    0.60{col 50}{space 3}0.546{col 58}{space 4}-.0410182{col 71}{space 3} .0774919
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0616027{col 30}{space 2} .0206318{col 41}{space 1}    2.99{col 50}{space 3}0.003{col 58}{space 4} .0211651{col 71}{space 3} .1020404
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0380214{col 30}{space 2} .0257873{col 41}{space 1}    1.47{col 50}{space 3}0.140{col 58}{space 4}-.0125207{col 71}{space 3} .0885635
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} -.048064{col 30}{space 2} .0220762{col 41}{space 1}   -2.18{col 50}{space 3}0.029{col 58}{space 4}-.0913325{col 71}{space 3}-.0047955
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0013239{col 30}{space 2} .0202923{col 41}{space 1}   -0.07{col 50}{space 3}0.948{col 58}{space 4}-.0410961{col 71}{space 3} .0384482
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0583418{col 30}{space 2} .0161332{col 41}{space 1}   -3.62{col 50}{space 3}0.000{col 58}{space 4}-.0899622{col 71}{space 3}-.0267214
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0047254{col 30}{space 2} .0010566{col 41}{space 1}    4.47{col 50}{space 3}0.000{col 58}{space 4} .0026544{col 71}{space 3} .0067963
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0001149{col 30}{space 2} .0210313{col 41}{space 1}   -0.01{col 50}{space 3}0.996{col 58}{space 4}-.0413356{col 71}{space 3} .0411057
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0857713{col 30}{space 2} .0441568{col 41}{space 1}    1.94{col 50}{space 3}0.052{col 58}{space 4}-.0007744{col 71}{space 3} .1723169
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0032274{col 30}{space 2} .0318717{col 41}{space 1}    0.10{col 50}{space 3}0.919{col 58}{space 4}-.0592399{col 71}{space 3} .0656946
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.1772262{col 30}{space 2} .0360228{col 41}{space 1}   -4.92{col 50}{space 3}0.000{col 58}{space 4}-.2478296{col 71}{space 3}-.1066228
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2002491{col 30}{space 2} .0343085{col 41}{space 1}   -5.84{col 50}{space 3}0.000{col 58}{space 4}-.2674926{col 71}{space 3}-.1330056
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2874018{col 30}{space 2} .0290331{col 41}{space 1}   -9.90{col 50}{space 3}0.000{col 58}{space 4}-.3443056{col 71}{space 3} -.230498
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.8686568{col 30}{space 2} .0557629{col 41}{space 1}  -15.58{col 50}{space 3}0.000{col 58}{space 4}-.9779501{col 71}{space 3}-.7593635
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2956424{col 30}{space 2} .0098027{col 41}{space 1}   30.16{col 50}{space 3}0.000{col 58}{space 4} .2764294{col 71}{space 3} .3148554
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2} 1.001525{col 30}{space 2} .0573341{col 41}{space 1}   17.47{col 50}{space 3}0.000{col 58}{space 4} .8891518{col 71}{space 3} 1.113897
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-.1550275{col 30}{space 2} .0303005{col 41}{space 1}   -5.12{col 50}{space 3}0.000{col 58}{space 4}-.2144154{col 71}{space 3}-.0956397
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2} 1.619034{col 30}{space 2} .0491038{col 41}{space 1}   32.97{col 50}{space 3}0.000{col 58}{space 4} 1.522792{col 71}{space 3} 1.715276
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2} 1.949655{col 30}{space 2} .1022437{col 41}{space 1}   19.07{col 50}{space 3}0.000{col 58}{space 4} 1.749261{col 71}{space 3} 2.150049
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .7901405{col 30}{space 2} .0366203{col 41}{space 1}   21.58{col 50}{space 3}0.000{col 58}{space 4}  .718366{col 71}{space 3}  .861915
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.0406725{col 30}{space 2} .0831892{col 41}{space 1}   -0.49{col 50}{space 3}0.625{col 58}{space 4}-.2037203{col 71}{space 3} .1223753
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0187206{col 30}{space 2}  .075011{col 41}{space 1}   -0.25{col 50}{space 3}0.803{col 58}{space 4}-.1657393{col 71}{space 3} .1282982
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .2181591{col 30}{space 2} .0764425{col 41}{space 1}    2.85{col 50}{space 3}0.004{col 58}{space 4} .0683346{col 71}{space 3} .3679836
{txt}{space 11}2012  {c |}{col 18}{res}{space 2}   .22813{col 30}{space 2} .0753149{col 41}{space 1}    3.03{col 50}{space 3}0.002{col 58}{space 4} .0805155{col 71}{space 3} .3757446
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1891007{col 30}{space 2} .0780983{col 41}{space 1}    2.42{col 50}{space 3}0.015{col 58}{space 4} .0360308{col 71}{space 3} .3421707
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.3568359{col 30}{space 2} .0782454{col 41}{space 1}   -4.56{col 50}{space 3}0.000{col 58}{space 4}-.5101942{col 71}{space 3}-.2034777
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .2172886{col 30}{space 2} .0772295{col 41}{space 1}    2.81{col 50}{space 3}0.005{col 58}{space 4} .0659216{col 71}{space 3} .3686556
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.1285456{col 30}{space 2} .0842097{col 41}{space 1}   -1.53{col 50}{space 3}0.127{col 58}{space 4}-.2935936{col 71}{space 3} .0365023
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .4920464{col 30}{space 2}  .079044{col 41}{space 1}    6.22{col 50}{space 3}0.000{col 58}{space 4} .3371231{col 71}{space 3} .6469697
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .1082985{col 30}{space 2} .0810313{col 41}{space 1}    1.34{col 50}{space 3}0.181{col 58}{space 4}-.0505198{col 71}{space 3} .2671169
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} .6630172{col 30}{space 2} .0961131{col 41}{space 1}    6.90{col 50}{space 3}0.000{col 58}{space 4} .4746391{col 71}{space 3} .8513954
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .39697825
         {txt}sigma_e {c |} {res} 1.0314853
             {txt}rho {c |} {res} .12900925{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,449
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,096

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0299                                         {txt}min = {res}         1
{txt}     between = {res}0.4035                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.3196                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  2785.09
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,096} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0744973{col 30}{space 2} .0127543{col 41}{space 1}    5.84{col 50}{space 3}0.000{col 58}{space 4} .0494993{col 71}{space 3} .0994953
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0365847{col 30}{space 2} .0078052{col 41}{space 1}    4.69{col 50}{space 3}0.000{col 58}{space 4} .0212867{col 71}{space 3} .0518826
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0093898{col 30}{space 2} .0586338{col 41}{space 1}    0.16{col 50}{space 3}0.873{col 58}{space 4}-.1055303{col 71}{space 3}   .12431
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0025158{col 30}{space 2} .0010844{col 41}{space 1}    2.32{col 50}{space 3}0.020{col 58}{space 4} .0003904{col 71}{space 3} .0046412
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0626933{col 30}{space 2} .0358125{col 41}{space 1}   -1.75{col 50}{space 3}0.080{col 58}{space 4}-.1328845{col 71}{space 3} .0074978
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0924226{col 30}{space 2} .0302354{col 41}{space 1}    3.06{col 50}{space 3}0.002{col 58}{space 4} .0331623{col 71}{space 3} .1516828
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2449515{col 30}{space 2} .1737152{col 41}{space 1}   -1.41{col 50}{space 3}0.159{col 58}{space 4} -.585427{col 71}{space 3}  .095524
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0337956{col 30}{space 2} .0408701{col 41}{space 1}    0.83{col 50}{space 3}0.408{col 58}{space 4}-.0463084{col 71}{space 3} .1138996
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.1590638{col 30}{space 2} .0495637{col 41}{space 1}   -3.21{col 50}{space 3}0.001{col 58}{space 4}-.2562068{col 71}{space 3}-.0619208
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0012748{col 30}{space 2} .0658817{col 41}{space 1}   -0.02{col 50}{space 3}0.985{col 58}{space 4}-.1304006{col 71}{space 3}  .127851
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0232284{col 30}{space 2} .0515901{col 41}{space 1}   -0.45{col 50}{space 3}0.653{col 58}{space 4}-.1243432{col 71}{space 3} .0778864
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1833514{col 30}{space 2}  .029051{col 41}{space 1}   -6.31{col 50}{space 3}0.000{col 58}{space 4}-.2402903{col 71}{space 3}-.1264126
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0174226{col 30}{space 2} .0068549{col 41}{space 1}    2.54{col 50}{space 3}0.011{col 58}{space 4} .0039872{col 71}{space 3}  .030858
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0288079{col 30}{space 2} .0312479{col 41}{space 1}   -0.92{col 50}{space 3}0.357{col 58}{space 4}-.0900526{col 71}{space 3} .0324368
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .3051539{col 30}{space 2} .2937873{col 41}{space 1}    1.04{col 50}{space 3}0.299{col 58}{space 4}-.2706587{col 71}{space 3} .8809665
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0386138{col 30}{space 2} .0564107{col 41}{space 1}   -0.68{col 50}{space 3}0.494{col 58}{space 4}-.1491767{col 71}{space 3} .0719491
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.2298652{col 30}{space 2} .0647341{col 41}{space 1}   -3.55{col 50}{space 3}0.000{col 58}{space 4}-.3567417{col 71}{space 3}-.1029888
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.3839562{col 30}{space 2} .1088604{col 41}{space 1}   -3.53{col 50}{space 3}0.000{col 58}{space 4}-.5973186{col 71}{space 3}-.1705937
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2213694{col 30}{space 2} .0651698{col 41}{space 1}   -3.40{col 50}{space 3}0.001{col 58}{space 4}   -.3491{col 71}{space 3}-.0936388
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.0205879{col 30}{space 2} .1489244{col 41}{space 1}   -0.14{col 50}{space 3}0.890{col 58}{space 4}-.3124743{col 71}{space 3} .2712985
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2639648{col 30}{space 2} .0153962{col 41}{space 1}   17.14{col 50}{space 3}0.000{col 58}{space 4} .2337889{col 71}{space 3} .2941408
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1586738{col 30}{space 2} .0347855{col 41}{space 1}   -4.56{col 50}{space 3}0.000{col 58}{space 4} -.226852{col 71}{space 3}-.0904955
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .4867683{col 30}{space 2} .1363957{col 41}{space 1}    3.57{col 50}{space 3}0.000{col 58}{space 4} .2194377{col 71}{space 3}  .754099
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .59405191
         {txt}sigma_e {c |} {res} .87776198
             {txt}rho {c |} {res} .31414372{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,598
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,401

{txt}R-sq:                                           Obs per group:
     within  = {res}0.1561                                         {txt}min = {res}         3
{txt}     between = {res}0.6452                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.4401                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  4410.83
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,401} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .3344377{col 30}{space 2} .0180835{col 41}{space 1}   18.49{col 50}{space 3}0.000{col 58}{space 4} .2989947{col 71}{space 3} .3698807
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0024394{col 30}{space 2} .0097824{col 41}{space 1}   -0.25{col 50}{space 3}0.803{col 58}{space 4}-.0216126{col 71}{space 3} .0167338
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0595152{col 30}{space 2} .0767802{col 41}{space 1}    0.78{col 50}{space 3}0.438{col 58}{space 4}-.0909711{col 71}{space 3} .2100015
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0043721{col 30}{space 2} .0015743{col 41}{space 1}    2.78{col 50}{space 3}0.005{col 58}{space 4} .0012865{col 71}{space 3} .0074577
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} -.085757{col 30}{space 2} .0452636{col 41}{space 1}   -1.89{col 50}{space 3}0.058{col 58}{space 4}-.1744719{col 71}{space 3}  .002958
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0473228{col 30}{space 2} .0452095{col 41}{space 1}    1.05{col 50}{space 3}0.295{col 58}{space 4}-.0412861{col 71}{space 3} .1359318
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .4145249{col 30}{space 2} .1440371{col 41}{space 1}    2.88{col 50}{space 3}0.004{col 58}{space 4} .1322174{col 71}{space 3} .6968325
{txt}{space 11}phone {c |}{col 18}{res}{space 2}-.0229789{col 30}{space 2} .0504931{col 41}{space 1}   -0.46{col 50}{space 3}0.649{col 58}{space 4}-.1219436{col 71}{space 3} .0759858
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0589338{col 30}{space 2} .0860666{col 41}{space 1}   -0.68{col 50}{space 3}0.494{col 58}{space 4}-.2276214{col 71}{space 3} .1097537
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0526767{col 30}{space 2} .0562379{col 41}{space 1}   -0.94{col 50}{space 3}0.349{col 58}{space 4} -.162901{col 71}{space 3} .0575476
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0715184{col 30}{space 2} .0444407{col 41}{space 1}    1.61{col 50}{space 3}0.108{col 58}{space 4}-.0155837{col 71}{space 3} .1586205
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1062061{col 30}{space 2} .0376355{col 41}{space 1}   -2.82{col 50}{space 3}0.005{col 58}{space 4}-.1799704{col 71}{space 3}-.0324418
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .1383004{col 30}{space 2} .0323916{col 41}{space 1}    4.27{col 50}{space 3}0.000{col 58}{space 4} .0748141{col 71}{space 3} .2017867
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2044398{col 30}{space 2} .0530014{col 41}{space 1}    3.86{col 50}{space 3}0.000{col 58}{space 4}  .100559{col 71}{space 3} .3083206
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} -.466176{col 30}{space 2} .2381339{col 41}{space 1}   -1.96{col 50}{space 3}0.050{col 58}{space 4}-.9329098{col 71}{space 3} .0005578
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0107476{col 30}{space 2} .0850495{col 41}{space 1}    0.13{col 50}{space 3}0.899{col 58}{space 4}-.1559462{col 71}{space 3} .1774415
{txt}electricity_mean {c |}{col 18}{res}{space 2} -.046685{col 30}{space 2} .1071105{col 41}{space 1}   -0.44{col 50}{space 3}0.663{col 58}{space 4}-.2566177{col 71}{space 3} .1632476
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0271703{col 30}{space 2} .0861084{col 41}{space 1}    0.32{col 50}{space 3}0.752{col 58}{space 4} -.141599{col 71}{space 3} .1959396
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2880475{col 30}{space 2} .0750703{col 41}{space 1}   -3.84{col 50}{space 3}0.000{col 58}{space 4}-.4351826{col 71}{space 3}-.1409124
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .4629831{col 30}{space 2} .1562408{col 41}{space 1}    2.96{col 50}{space 3}0.003{col 58}{space 4} .1567568{col 71}{space 3} .7692093
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .3588126{col 30}{space 2} .0241185{col 41}{space 1}   14.88{col 50}{space 3}0.000{col 58}{space 4} .3115413{col 71}{space 3} .4060839
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .8302154{col 30}{space 2} .1014486{col 41}{space 1}    8.18{col 50}{space 3}0.000{col 58}{space 4} .6313797{col 71}{space 3} 1.029051
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .4469146{col 30}{space 2} .0645422{col 41}{space 1}    6.92{col 50}{space 3}0.000{col 58}{space 4} .3204141{col 71}{space 3}  .573415
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.7002508{col 30}{space 2}  .229856{col 41}{space 1}   -3.05{col 50}{space 3}0.002{col 58}{space 4} -1.15076{col 71}{space 3}-.2497413
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .4747934
         {txt}sigma_e {c |} {res} 1.0990003
             {txt}rho {c |} {res} .15728719{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,952
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,977

{txt}R-sq:                                           Obs per group:
     within  = {res}0.1985                                         {txt}min = {res}         1
{txt}     between = {res}0.5106                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.4184                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}  4252.12
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,977} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1000258{col 30}{space 2}  .023492{col 41}{space 1}    4.26{col 50}{space 3}0.000{col 58}{space 4} .0539824{col 71}{space 3} .1460692
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0345612{col 30}{space 2} .0046209{col 41}{space 1}   -7.48{col 50}{space 3}0.000{col 58}{space 4}-.0436181{col 71}{space 3}-.0255043
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0108209{col 30}{space 2} .0541932{col 41}{space 1}   -0.20{col 50}{space 3}0.842{col 58}{space 4}-.1170376{col 71}{space 3} .0953959
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0092579{col 30}{space 2} .0011321{col 41}{space 1}   -8.18{col 50}{space 3}0.000{col 58}{space 4}-.0114768{col 71}{space 3}-.0070389
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1510757{col 30}{space 2} .0286591{col 41}{space 1}   -5.27{col 50}{space 3}0.000{col 58}{space 4}-.2072465{col 71}{space 3}-.0949049
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0374471{col 30}{space 2} .0269096{col 41}{space 1}    1.39{col 50}{space 3}0.164{col 58}{space 4}-.0152948{col 71}{space 3}  .090189
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0021874{col 30}{space 2} .0420263{col 41}{space 1}    0.05{col 50}{space 3}0.958{col 58}{space 4}-.0801828{col 71}{space 3} .0845575
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0027412{col 30}{space 2}  .040529{col 41}{space 1}    0.07{col 50}{space 3}0.946{col 58}{space 4}-.0766942{col 71}{space 3} .0821767
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2105317{col 30}{space 2} .0397964{col 41}{space 1}    5.29{col 50}{space 3}0.000{col 58}{space 4} .1325321{col 71}{space 3} .2885312
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .074599{col 30}{space 2} .0424718{col 41}{space 1}    1.76{col 50}{space 3}0.079{col 58}{space 4}-.0086441{col 71}{space 3} .1578422
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0635585{col 30}{space 2} .0371468{col 41}{space 1}   -1.71{col 50}{space 3}0.087{col 58}{space 4} -.136365{col 71}{space 3} .0092479
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0391656{col 30}{space 2} .0301203{col 41}{space 1}   -1.30{col 50}{space 3}0.193{col 58}{space 4}-.0982004{col 71}{space 3} .0198691
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0066104{col 30}{space 2} .0013699{col 41}{space 1}    4.83{col 50}{space 3}0.000{col 58}{space 4} .0039255{col 71}{space 3} .0092953
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1179639{col 30}{space 2} .1578392{col 41}{space 1}    0.75{col 50}{space 3}0.455{col 58}{space 4}-.1913953{col 71}{space 3} .4273231
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0690967{col 30}{space 2} .0552085{col 41}{space 1}   -1.25{col 50}{space 3}0.211{col 58}{space 4}-.1773034{col 71}{space 3}   .03911
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.1029166{col 30}{space 2} .0536302{col 41}{space 1}   -1.92{col 50}{space 3}0.055{col 58}{space 4}-.2080298{col 71}{space 3} .0021966
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.2409991{col 30}{space 2} .0541422{col 41}{space 1}   -4.45{col 50}{space 3}0.000{col 58}{space 4}-.3471159{col 71}{space 3}-.1348824
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0922638{col 30}{space 2} .0515444{col 41}{space 1}   -1.79{col 50}{space 3}0.073{col 58}{space 4} -.193289{col 71}{space 3} .0087613
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0354686{col 30}{space 2}  .048261{col 41}{space 1}   -0.73{col 50}{space 3}0.462{col 58}{space 4}-.1300583{col 71}{space 3} .0591212
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-2.566828{col 30}{space 2} .2182695{col 41}{space 1}  -11.76{col 50}{space 3}0.000{col 58}{space 4}-2.994628{col 71}{space 3}-2.139027
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2332192{col 30}{space 2} .0236722{col 41}{space 1}    9.85{col 50}{space 3}0.000{col 58}{space 4} .1868225{col 71}{space 3}  .279616
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}   1.0968{col 30}{space 2} .0721507{col 41}{space 1}   15.20{col 50}{space 3}0.000{col 58}{space 4} .9553869{col 71}{space 3} 1.238212
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.118649{col 30}{space 2} .1039915{col 41}{space 1}   10.76{col 50}{space 3}0.000{col 58}{space 4} .9148292{col 71}{space 3} 1.322469
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .35154427
         {txt}sigma_e {c |} {res} .74290756
             {txt}rho {c |} {res} .18295231{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,770
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,203

{txt}R-sq:                                           Obs per group:
     within  = {res}0.1242                                         {txt}min = {res}         3
{txt}     between = {res}0.6508                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.4233                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  3838.45
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,203} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}-.0352351{col 30}{space 2} .1212437{col 41}{space 1}   -0.29{col 50}{space 3}0.771{col 58}{space 4}-.2728683{col 71}{space 3} .2023982
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0602061{col 30}{space 2} .0384877{col 41}{space 1}   -1.56{col 50}{space 3}0.118{col 58}{space 4}-.1356406{col 71}{space 3} .0152285
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1268526{col 30}{space 2} .0683016{col 41}{space 1}   -1.86{col 50}{space 3}0.063{col 58}{space 4}-.2607212{col 71}{space 3} .0070161
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0200062{col 30}{space 2} .0095289{col 41}{space 1}   -2.10{col 50}{space 3}0.036{col 58}{space 4}-.0386825{col 71}{space 3}-.0013299
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0270784{col 30}{space 2} .0485389{col 41}{space 1}   -0.56{col 50}{space 3}0.577{col 58}{space 4}-.1222129{col 71}{space 3}  .068056
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} -.077574{col 30}{space 2} .0433552{col 41}{space 1}   -1.79{col 50}{space 3}0.074{col 58}{space 4}-.1625487{col 71}{space 3} .0074006
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0778742{col 30}{space 2} .0503687{col 41}{space 1}   -1.55{col 50}{space 3}0.122{col 58}{space 4} -.176595{col 71}{space 3} .0208466
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2061961{col 30}{space 2} .0796417{col 41}{space 1}    2.59{col 50}{space 3}0.010{col 58}{space 4} .0501013{col 71}{space 3} .3622909
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2291878{col 30}{space 2}  .153005{col 41}{space 1}    1.50{col 50}{space 3}0.134{col 58}{space 4}-.0706965{col 71}{space 3}  .529072
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1161597{col 30}{space 2} .0594365{col 41}{space 1}    1.95{col 50}{space 3}0.051{col 58}{space 4}-.0003338{col 71}{space 3} .2326532
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0488795{col 30}{space 2} .0646657{col 41}{space 1}   -0.76{col 50}{space 3}0.450{col 58}{space 4}-.1756218{col 71}{space 3} .0778629
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.050841{col 30}{space 2} .0694972{col 41}{space 1}   -0.73{col 50}{space 3}0.464{col 58}{space 4}-.1870529{col 71}{space 3}  .085371
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0394326{col 30}{space 2} .0135405{col 41}{space 1}    2.91{col 50}{space 3}0.004{col 58}{space 4} .0128937{col 71}{space 3} .0659716
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.3263201{col 30}{space 2} .1899987{col 41}{space 1}   -1.72{col 50}{space 3}0.086{col 58}{space 4}-.6987107{col 71}{space 3} .0460705
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0985783{col 30}{space 2} .0710458{col 41}{space 1}    1.39{col 50}{space 3}0.165{col 58}{space 4} -.040669{col 71}{space 3} .2378255
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1240658{col 30}{space 2}  .084993{col 41}{space 1}    1.46{col 50}{space 3}0.144{col 58}{space 4}-.0425174{col 71}{space 3}  .290649
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.3315027{col 30}{space 2} .0813318{col 41}{space 1}   -4.08{col 50}{space 3}0.000{col 58}{space 4}  -.49091{col 71}{space 3}-.1720954
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.3317956{col 30}{space 2} .0771013{col 41}{space 1}   -4.30{col 50}{space 3}0.000{col 58}{space 4}-.4829114{col 71}{space 3}-.1806798
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.3158423{col 30}{space 2}  .069502{col 41}{space 1}   -4.54{col 50}{space 3}0.000{col 58}{space 4}-.4520638{col 71}{space 3}-.1796209
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-2.651852{col 30}{space 2} 1.244367{col 41}{space 1}   -2.13{col 50}{space 3}0.033{col 58}{space 4}-5.090767{col 71}{space 3}-.2129369
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2253159{col 30}{space 2} .0260997{col 41}{space 1}    8.63{col 50}{space 3}0.000{col 58}{space 4} .1741614{col 71}{space 3} .2764704
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.4082141{col 30}{space 2} .0923006{col 41}{space 1}   -4.42{col 50}{space 3}0.000{col 58}{space 4}  -.58912{col 71}{space 3}-.2273083
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.1874262{col 30}{space 2} .0906486{col 41}{space 1}   -2.07{col 50}{space 3}0.039{col 58}{space 4}-.3650943{col 71}{space 3}-.0097581
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3669061{col 30}{space 2} .0455208{col 41}{space 1}   -8.06{col 50}{space 3}0.000{col 58}{space 4}-.4561253{col 71}{space 3}-.2776869
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 6.057811{col 30}{space 2} 2.394151{col 41}{space 1}    2.53{col 50}{space 3}0.011{col 58}{space 4} 1.365362{col 71}{space 3} 10.75026
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .34684049
         {txt}sigma_e {c |} {res} .92166933
             {txt}rho {c |} {res} .12404796{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     1,582
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}       317

{txt}R-sq:                                           Obs per group:
     within  = {res}0.1585                                         {txt}min = {res}         4
{txt}     between = {res}0.7037                                         {txt}avg = {res}       5.0
{txt}     overall = {res}0.4911                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1490.84
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:317} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}-.0222203{col 30}{space 2} .2230776{col 41}{space 1}   -0.10{col 50}{space 3}0.921{col 58}{space 4}-.4594443{col 71}{space 3} .4150038
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.1067415{col 30}{space 2} .0620995{col 41}{space 1}   -1.72{col 50}{space 3}0.086{col 58}{space 4}-.2284543{col 71}{space 3} .0149712
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0494284{col 30}{space 2} .1579661{col 41}{space 1}   -0.31{col 50}{space 3}0.754{col 58}{space 4}-.3590363{col 71}{space 3} .2601795
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0306196{col 30}{space 2} .0164456{col 41}{space 1}   -1.86{col 50}{space 3}0.063{col 58}{space 4}-.0628524{col 71}{space 3} .0016132
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1328654{col 30}{space 2} .0892932{col 41}{space 1}    1.49{col 50}{space 3}0.137{col 58}{space 4} -.042146{col 71}{space 3} .3078768
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0049552{col 30}{space 2} .0896336{col 41}{space 1}    0.06{col 50}{space 3}0.956{col 58}{space 4}-.1707235{col 71}{space 3} .1806338
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1385282{col 30}{space 2} .1273608{col 41}{space 1}    1.09{col 50}{space 3}0.277{col 58}{space 4}-.1110943{col 71}{space 3} .3881507
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1027961{col 30}{space 2} .1498415{col 41}{space 1}    0.69{col 50}{space 3}0.493{col 58}{space 4} -.190888{col 71}{space 3} .3964801
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1834148{col 30}{space 2} .2650846{col 41}{space 1}    0.69{col 50}{space 3}0.489{col 58}{space 4}-.3361415{col 71}{space 3} .7029711
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0935789{col 30}{space 2} .0869233{col 41}{space 1}    1.08{col 50}{space 3}0.282{col 58}{space 4}-.0767876{col 71}{space 3} .2639454
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0263322{col 30}{space 2} .1108602{col 41}{space 1}    0.24{col 50}{space 3}0.812{col 58}{space 4}-.1909498{col 71}{space 3} .2436143
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1983421{col 30}{space 2} .0888016{col 41}{space 1}   -2.23{col 50}{space 3}0.026{col 58}{space 4}  -.37239{col 71}{space 3}-.0242942
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0353633{col 30}{space 2} .0162045{col 41}{space 1}    2.18{col 50}{space 3}0.029{col 58}{space 4}  .003603{col 71}{space 3} .0671236
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.3770774{col 30}{space 2} .3285495{col 41}{space 1}   -1.15{col 50}{space 3}0.251{col 58}{space 4}-1.021023{col 71}{space 3} .2668678
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.1608796{col 30}{space 2} .2352837{col 41}{space 1}   -0.68{col 50}{space 3}0.494{col 58}{space 4}-.6220272{col 71}{space 3}  .300268
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0126244{col 30}{space 2} .1957653{col 41}{space 1}   -0.06{col 50}{space 3}0.949{col 58}{space 4}-.3963173{col 71}{space 3} .3710685
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4860992{col 30}{space 2} .1824999{col 41}{space 1}    2.66{col 50}{space 3}0.008{col 58}{space 4} .1284059{col 71}{space 3} .8437924
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1531384{col 30}{space 2} .1444427{col 41}{space 1}   -1.06{col 50}{space 3}0.289{col 58}{space 4}-.4362409{col 71}{space 3} .1299641
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.5511205{col 30}{space 2} .1560388{col 41}{space 1}   -3.53{col 50}{space 3}0.000{col 58}{space 4}-.8569509{col 71}{space 3}-.2452901
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-3.374653{col 30}{space 2} 1.968321{col 41}{space 1}   -1.71{col 50}{space 3}0.086{col 58}{space 4}-7.232492{col 71}{space 3} .4831855
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2761816{col 30}{space 2} .0381692{col 41}{space 1}    7.24{col 50}{space 3}0.000{col 58}{space 4} .2013713{col 71}{space 3} .3509919
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.2747948{col 30}{space 2} .2755446{col 41}{space 1}   -1.00{col 50}{space 3}0.319{col 58}{space 4}-.8148524{col 71}{space 3} .2652628
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .4535768{col 30}{space 2} .1319305{col 41}{space 1}    3.44{col 50}{space 3}0.001{col 58}{space 4} .1949977{col 71}{space 3} .7121559
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.1240272{col 30}{space 2} .2152072{col 41}{space 1}   -0.58{col 50}{space 3}0.564{col 58}{space 4}-.5458255{col 71}{space 3} .2977711
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 9.654966{col 30}{space 2} 5.528886{col 41}{space 1}    1.75{col 50}{space 3}0.081{col 58}{space 4}-1.181451{col 71}{space 3} 20.49138
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .50748059
         {txt}sigma_e {c |} {res} 1.0427962
             {txt}rho {c |} {res} .19148262{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,801
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,115

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0743                                         {txt}min = {res}         6
{txt}     between = {res}0.7132                                         {txt}avg = {res}       7.0
{txt}     overall = {res}0.4322                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}  4573.50
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,115} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}-.0281124{col 30}{space 2} .0604467{col 41}{space 1}   -0.47{col 50}{space 3}0.642{col 58}{space 4}-.1465858{col 71}{space 3}  .090361
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0523944{col 30}{space 2} .0201305{col 41}{space 1}   -2.60{col 50}{space 3}0.009{col 58}{space 4}-.0918495{col 71}{space 3}-.0129394
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0330976{col 30}{space 2} .0753812{col 41}{space 1}   -0.44{col 50}{space 3}0.661{col 58}{space 4} -.180842{col 71}{space 3} .1146469
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0170581{col 30}{space 2} .0050571{col 41}{space 1}   -3.37{col 50}{space 3}0.001{col 58}{space 4}-.0269699{col 71}{space 3}-.0071463
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0522207{col 30}{space 2} .0458098{col 41}{space 1}   -1.14{col 50}{space 3}0.254{col 58}{space 4}-.1420063{col 71}{space 3} .0375649
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1142138{col 30}{space 2} .0464242{col 41}{space 1}    2.46{col 50}{space 3}0.014{col 58}{space 4}  .023224{col 71}{space 3} .2052037
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0339464{col 30}{space 2}   .06913{col 41}{space 1}   -0.49{col 50}{space 3}0.623{col 58}{space 4}-.1694387{col 71}{space 3}  .101546
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2062526{col 30}{space 2} .0524243{col 41}{space 1}    3.93{col 50}{space 3}0.000{col 58}{space 4} .1035029{col 71}{space 3} .3090022
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3324343{col 30}{space 2} .0717245{col 41}{space 1}    4.63{col 50}{space 3}0.000{col 58}{space 4} .1918568{col 71}{space 3} .4730118
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.1324151{col 30}{space 2} .0392758{col 41}{space 1}   -3.37{col 50}{space 3}0.001{col 58}{space 4}-.2093943{col 71}{space 3}-.0554359
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1044334{col 30}{space 2} .0455396{col 41}{space 1}   -2.29{col 50}{space 3}0.022{col 58}{space 4}-.1936893{col 71}{space 3}-.0151775
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0834247{col 30}{space 2} .0360814{col 41}{space 1}   -2.31{col 50}{space 3}0.021{col 58}{space 4} -.154143{col 71}{space 3}-.0127063
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0124778{col 30}{space 2} .0034227{col 41}{space 1}    3.65{col 50}{space 3}0.000{col 58}{space 4} .0057694{col 71}{space 3} .0191861
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.1652773{col 30}{space 2} .0980982{col 41}{space 1}   -1.68{col 50}{space 3}0.092{col 58}{space 4}-.3575461{col 71}{space 3} .0269916
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0493422{col 30}{space 2}  .126093{col 41}{space 1}    0.39{col 50}{space 3}0.696{col 58}{space 4}-.1977955{col 71}{space 3}   .29648
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1380861{col 30}{space 2} .0919806{col 41}{space 1}    1.50{col 50}{space 3}0.133{col 58}{space 4}-.0421926{col 71}{space 3} .3183647
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0066526{col 30}{space 2} .1066841{col 41}{space 1}    0.06{col 50}{space 3}0.950{col 58}{space 4}-.2024445{col 71}{space 3} .2157496
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1945306{col 30}{space 2} .0807934{col 41}{space 1}   -2.41{col 50}{space 3}0.016{col 58}{space 4}-.3528827{col 71}{space 3}-.0361785
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.3507549{col 30}{space 2} .0774551{col 41}{space 1}   -4.53{col 50}{space 3}0.000{col 58}{space 4}-.5025642{col 71}{space 3}-.1989456
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-2.777079{col 30}{space 2}  .697056{col 41}{space 1}   -3.98{col 50}{space 3}0.000{col 58}{space 4}-4.143284{col 71}{space 3}-1.410874
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .5200586{col 30}{space 2} .0240479{col 41}{space 1}   21.63{col 50}{space 3}0.000{col 58}{space 4} .4729256{col 71}{space 3} .5671915
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} -.362381{col 30}{space 2} .0933839{col 41}{space 1}   -3.88{col 50}{space 3}0.000{col 58}{space 4}-.5454101{col 71}{space 3}-.1793519
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .1043965{col 30}{space 2} .0434907{col 41}{space 1}    2.40{col 50}{space 3}0.016{col 58}{space 4} .0191564{col 71}{space 3} .1896367
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .5007207{col 30}{space 2} .0510792{col 41}{space 1}    9.80{col 50}{space 3}0.000{col 58}{space 4} .4006073{col 71}{space 3} .6008342
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .3992246{col 30}{space 2} .0625089{col 41}{space 1}    6.39{col 50}{space 3}0.000{col 58}{space 4} .2767095{col 71}{space 3} .5217397
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .4471891{col 30}{space 2}  .050143{col 41}{space 1}    8.92{col 50}{space 3}0.000{col 58}{space 4} .3489106{col 71}{space 3} .5454676
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.757136{col 30}{space 2} 1.239011{col 41}{space 1}    3.84{col 50}{space 3}0.000{col 58}{space 4} 2.328719{col 71}{space 3} 7.185553
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .51587168
         {txt}sigma_e {c |} {res} 1.1845907
             {txt}rho {c |} {res} .15941475{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S13_balance_imr.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean _cons)
{res}{txt}(note: file S13_balance_imr.rtf not found)
(output written to {browse  `"S13_balance_imr.rtf"'})

{com}. 
. 
. 
. eststo clear
{txt}
{com}. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    33,152
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    10,109

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0362                                         {txt}min = {res}         1
{txt}     between = {res}0.6244                                         {txt}avg = {res}       3.3
{txt}     overall = {res}0.4581                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 20733.45
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:10,109} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0170949{col 30}{space 2} .0097957{col 41}{space 1}    1.75{col 50}{space 3}0.081{col 58}{space 4}-.0021043{col 71}{space 3} .0362942
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0084149{col 30}{space 2}  .004572{col 41}{space 1}    1.84{col 50}{space 3}0.066{col 58}{space 4}-.0005461{col 71}{space 3} .0173759
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1119978{col 30}{space 2} .0455433{col 41}{space 1}   -2.46{col 50}{space 3}0.014{col 58}{space 4} -.201261{col 71}{space 3}-.0227346
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0036724{col 30}{space 2} .0009127{col 41}{space 1}   -4.02{col 50}{space 3}0.000{col 58}{space 4}-.0054613{col 71}{space 3}-.0018834
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0221302{col 30}{space 2} .0288552{col 41}{space 1}   -0.77{col 50}{space 3}0.443{col 58}{space 4}-.0786854{col 71}{space 3} .0344251
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2107619{col 30}{space 2} .0234355{col 41}{space 1}    8.99{col 50}{space 3}0.000{col 58}{space 4}  .164829{col 71}{space 3} .2566947
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1565375{col 30}{space 2} .0431069{col 41}{space 1}    3.63{col 50}{space 3}0.000{col 58}{space 4} .0720495{col 71}{space 3} .2410255
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2038544{col 30}{space 2} .0281314{col 41}{space 1}    7.25{col 50}{space 3}0.000{col 58}{space 4} .1487179{col 71}{space 3}  .258991
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2759455{col 30}{space 2} .0336758{col 41}{space 1}    8.19{col 50}{space 3}0.000{col 58}{space 4} .2099421{col 71}{space 3} .3419489
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2183525{col 30}{space 2} .0294625{col 41}{space 1}    7.41{col 50}{space 3}0.000{col 58}{space 4} .1606072{col 71}{space 3} .2760979
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2402619{col 30}{space 2} .0266659{col 41}{space 1}    9.01{col 50}{space 3}0.000{col 58}{space 4} .1879976{col 71}{space 3} .2925262
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0460873{col 30}{space 2}    .0216{col 41}{space 1}   -2.13{col 50}{space 3}0.033{col 58}{space 4}-.0884225{col 71}{space 3}-.0037521
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0004332{col 30}{space 2} .0014605{col 41}{space 1}   -0.30{col 50}{space 3}0.767{col 58}{space 4}-.0032957{col 71}{space 3} .0024293
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0434579{col 30}{space 2} .0274077{col 41}{space 1}    1.59{col 50}{space 3}0.113{col 58}{space 4}-.0102601{col 71}{space 3} .0971759
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.1282281{col 30}{space 2} .0681819{col 41}{space 1}   -1.88{col 50}{space 3}0.060{col 58}{space 4}-.2618621{col 71}{space 3} .0054059
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6509688{col 30}{space 2} .0468116{col 41}{space 1}   13.91{col 50}{space 3}0.000{col 58}{space 4} .5592198{col 71}{space 3} .7427179
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8678234{col 30}{space 2} .0532779{col 41}{space 1}   16.29{col 50}{space 3}0.000{col 58}{space 4} .7634007{col 71}{space 3} .9722461
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .5800336{col 30}{space 2}  .054385{col 41}{space 1}   10.67{col 50}{space 3}0.000{col 58}{space 4}  .473441{col 71}{space 3} .6866261
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .5558234{col 30}{space 2} .0429609{col 41}{space 1}   12.94{col 50}{space 3}0.000{col 58}{space 4} .4716215{col 71}{space 3} .6400253
{txt}{space 13}imr {c |}{col 18}{res}{space 2}  .256076{col 30}{space 2} .0797328{col 41}{space 1}    3.21{col 50}{space 3}0.001{col 58}{space 4} .0998027{col 71}{space 3} .4123493
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1614598{col 30}{space 2}  .013109{col 41}{space 1}  -12.32{col 50}{space 3}0.000{col 58}{space 4}-.1871531{col 71}{space 3}-.1357666
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.9230807{col 30}{space 2} .0838758{col 41}{space 1}  -11.01{col 50}{space 3}0.000{col 58}{space 4}-1.087474{col 71}{space 3}-.7586871
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-2.042957{col 30}{space 2} .0467706{col 41}{space 1}  -43.68{col 50}{space 3}0.000{col 58}{space 4}-2.134625{col 71}{space 3}-1.951288
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-1.677313{col 30}{space 2} .0697666{col 41}{space 1}  -24.04{col 50}{space 3}0.000{col 58}{space 4}-1.814053{col 71}{space 3}-1.540573
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-1.486892{col 30}{space 2} .1496504{col 41}{space 1}   -9.94{col 50}{space 3}0.000{col 58}{space 4}-1.780202{col 71}{space 3}-1.193583
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2}-.2633713{col 30}{space 2}  .055556{col 41}{space 1}   -4.74{col 50}{space 3}0.000{col 58}{space 4} -.372259{col 71}{space 3}-.1544835
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.3249937{col 30}{space 2} .1047738{col 41}{space 1}   -3.10{col 50}{space 3}0.002{col 58}{space 4}-.5303465{col 71}{space 3}-.1196409
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.1152619{col 30}{space 2} .0942132{col 41}{space 1}   -1.22{col 50}{space 3}0.221{col 58}{space 4}-.2999163{col 71}{space 3} .0693925
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}-.0751376{col 30}{space 2} .0963097{col 41}{space 1}   -0.78{col 50}{space 3}0.435{col 58}{space 4}-.2639011{col 71}{space 3} .1136259
{txt}{space 11}2012  {c |}{col 18}{res}{space 2}-.1024588{col 30}{space 2} .0961544{col 41}{space 1}   -1.07{col 50}{space 3}0.287{col 58}{space 4} -.290918{col 71}{space 3} .0860005
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0375324{col 30}{space 2} .0984291{col 41}{space 1}    0.38{col 50}{space 3}0.703{col 58}{space 4}-.1553851{col 71}{space 3} .2304499
{txt}{space 11}2014  {c |}{col 18}{res}{space 2} .0246623{col 30}{space 2} .0996839{col 41}{space 1}    0.25{col 50}{space 3}0.805{col 58}{space 4}-.1707144{col 71}{space 3} .2200391
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .2187113{col 30}{space 2} .0978531{col 41}{space 1}    2.24{col 50}{space 3}0.025{col 58}{space 4} .0269227{col 71}{space 3} .4104999
{txt}{space 11}2016  {c |}{col 18}{res}{space 2} .0302522{col 30}{space 2} .1093293{col 41}{space 1}    0.28{col 50}{space 3}0.782{col 58}{space 4}-.1840292{col 71}{space 3} .2445336
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .2523658{col 30}{space 2} .1007438{col 41}{space 1}    2.51{col 50}{space 3}0.012{col 58}{space 4} .0549116{col 71}{space 3}   .44982
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .1445932{col 30}{space 2} .1034113{col 41}{space 1}    1.40{col 50}{space 3}0.162{col 58}{space 4}-.0580893{col 71}{space 3} .3472756
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.170831{col 30}{space 2} .1283535{col 41}{space 1}   32.49{col 50}{space 3}0.000{col 58}{space 4} 3.919263{col 71}{space 3} 4.422399
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .83040921
         {txt}sigma_e {c |} {res} 1.3768361
             {txt}rho {c |} {res} .26673535{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,449
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,096

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0497                                         {txt}min = {res}         1
{txt}     between = {res}0.3610                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2914                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1897.19
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,096} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0914601{col 30}{space 2} .0144714{col 41}{space 1}    6.32{col 50}{space 3}0.000{col 58}{space 4} .0630967{col 71}{space 3} .1198235
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0437387{col 30}{space 2} .0102023{col 41}{space 1}    4.29{col 50}{space 3}0.000{col 58}{space 4} .0237425{col 71}{space 3} .0637349
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0402201{col 30}{space 2} .0809886{col 41}{space 1}    0.50{col 50}{space 3}0.619{col 58}{space 4}-.1185146{col 71}{space 3} .1989548
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0012424{col 30}{space 2} .0014636{col 41}{space 1}    0.85{col 50}{space 3}0.396{col 58}{space 4}-.0016263{col 71}{space 3}  .004111
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0239935{col 30}{space 2} .0497618{col 41}{space 1}    0.48{col 50}{space 3}0.630{col 58}{space 4}-.0735378{col 71}{space 3} .1215248
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2310997{col 30}{space 2} .0398643{col 41}{space 1}    5.80{col 50}{space 3}0.000{col 58}{space 4}  .152967{col 71}{space 3} .3092324
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1021454{col 30}{space 2} .1931308{col 41}{space 1}    0.53{col 50}{space 3}0.597{col 58}{space 4}-.2763841{col 71}{space 3} .4806748
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0674915{col 30}{space 2} .0493792{col 41}{space 1}    1.37{col 50}{space 3}0.172{col 58}{space 4}-.0292899{col 71}{space 3}  .164273
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1363257{col 30}{space 2} .0614351{col 41}{space 1}    2.22{col 50}{space 3}0.026{col 58}{space 4} .0159152{col 71}{space 3} .2567362
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0167716{col 30}{space 2} .0859483{col 41}{space 1}    0.20{col 50}{space 3}0.845{col 58}{space 4} -.151684{col 71}{space 3} .1852272
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3007643{col 30}{space 2} .0660906{col 41}{space 1}    4.55{col 50}{space 3}0.000{col 58}{space 4} .1712291{col 71}{space 3} .4302994
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1253858{col 30}{space 2} .0368822{col 41}{space 1}   -3.40{col 50}{space 3}0.001{col 58}{space 4}-.1976737{col 71}{space 3} -.053098
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0121655{col 30}{space 2} .0057163{col 41}{space 1}   -2.13{col 50}{space 3}0.033{col 58}{space 4}-.0233692{col 71}{space 3}-.0009618
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .389828{col 30}{space 2} .0397006{col 41}{space 1}    9.82{col 50}{space 3}0.000{col 58}{space 4} .3120163{col 71}{space 3} .4676397
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2571294{col 30}{space 2} .3579872{col 41}{space 1}    0.72{col 50}{space 3}0.473{col 58}{space 4}-.4445125{col 71}{space 3} .9587714
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5616854{col 30}{space 2} .0735717{col 41}{space 1}    7.63{col 50}{space 3}0.000{col 58}{space 4} .4174875{col 71}{space 3} .7058833
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7466537{col 30}{space 2} .0882774{col 41}{space 1}    8.46{col 50}{space 3}0.000{col 58}{space 4} .5736333{col 71}{space 3} .9196742
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .7541074{col 30}{space 2} .1542762{col 41}{space 1}    4.89{col 50}{space 3}0.000{col 58}{space 4} .4517317{col 71}{space 3} 1.056483
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4518174{col 30}{space 2} .0852658{col 41}{space 1}    5.30{col 50}{space 3}0.000{col 58}{space 4} .2846996{col 71}{space 3} .6189353
{txt}{space 13}imr {c |}{col 18}{res}{space 2} 2.011331{col 30}{space 2} .1970934{col 41}{space 1}   10.20{col 50}{space 3}0.000{col 58}{space 4} 1.625035{col 71}{space 3} 2.397627
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0752006{col 30}{space 2} .0197153{col 41}{space 1}   -3.81{col 50}{space 3}0.000{col 58}{space 4}-.1138419{col 71}{space 3}-.0365593
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.5431176{col 30}{space 2}  .041929{col 41}{space 1}  -12.95{col 50}{space 3}0.000{col 58}{space 4} -.625297{col 71}{space 3}-.4609383
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .6371893{col 30}{space 2} .1849705{col 41}{space 1}    3.44{col 50}{space 3}0.001{col 58}{space 4} .2746538{col 71}{space 3} .9997248
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .83937095
         {txt}sigma_e {c |} {res}  1.066031
             {txt}rho {c |} {res} .38270327{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,598
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,401

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0433                                         {txt}min = {res}         3
{txt}     between = {res}0.6499                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.4556                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  3876.22
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,401} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0006959{col 30}{space 2} .0219299{col 41}{space 1}    0.03{col 50}{space 3}0.975{col 58}{space 4} -.042286{col 71}{space 3} .0436777
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0147508{col 30}{space 2}  .013021{col 41}{space 1}    1.13{col 50}{space 3}0.257{col 58}{space 4}  -.01077{col 71}{space 3} .0402716
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.3930653{col 30}{space 2} .1053253{col 41}{space 1}   -3.73{col 50}{space 3}0.000{col 58}{space 4}-.5994991{col 71}{space 3}-.1866315
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0068328{col 30}{space 2} .0023058{col 41}{space 1}   -2.96{col 50}{space 3}0.003{col 58}{space 4}-.0113521{col 71}{space 3}-.0023135
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.2072718{col 30}{space 2} .0666355{col 41}{space 1}   -3.11{col 50}{space 3}0.002{col 58}{space 4}-.3378749{col 71}{space 3}-.0766687
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2652838{col 30}{space 2} .0632876{col 41}{space 1}    4.19{col 50}{space 3}0.000{col 58}{space 4} .1412423{col 71}{space 3} .3893252
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0920808{col 30}{space 2} .1595205{col 41}{space 1}    0.58{col 50}{space 3}0.564{col 58}{space 4}-.2205736{col 71}{space 3} .4047352
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3055112{col 30}{space 2} .0710217{col 41}{space 1}    4.30{col 50}{space 3}0.000{col 58}{space 4} .1663111{col 71}{space 3} .4447112
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4782842{col 30}{space 2} .1191716{col 41}{space 1}    4.01{col 50}{space 3}0.000{col 58}{space 4} .2447122{col 71}{space 3} .7118561
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2780941{col 30}{space 2} .0761724{col 41}{space 1}    3.65{col 50}{space 3}0.000{col 58}{space 4} .1287989{col 71}{space 3} .4273892
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3508077{col 30}{space 2} .0567777{col 41}{space 1}    6.18{col 50}{space 3}0.000{col 58}{space 4} .2395254{col 71}{space 3}   .46209
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0334114{col 30}{space 2} .0498967{col 41}{space 1}   -0.67{col 50}{space 3}0.503{col 58}{space 4}-.1312072{col 71}{space 3} .0643844
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0116008{col 30}{space 2} .0354349{col 41}{space 1}   -0.33{col 50}{space 3}0.743{col 58}{space 4}-.0810521{col 71}{space 3} .0578504
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0282684{col 30}{space 2} .0698983{col 41}{space 1}    0.40{col 50}{space 3}0.686{col 58}{space 4}-.1087299{col 71}{space 3} .1652666
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1988562{col 30}{space 2} .3686317{col 41}{space 1}    0.54{col 50}{space 3}0.590{col 58}{space 4}-.5236486{col 71}{space 3} .9213609
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .8298772{col 30}{space 2} .1299884{col 41}{space 1}    6.38{col 50}{space 3}0.000{col 58}{space 4} .5751047{col 71}{space 3}  1.08465
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.049326{col 30}{space 2} .1690915{col 41}{space 1}    6.21{col 50}{space 3}0.000{col 58}{space 4} .7179132{col 71}{space 3}  1.38074
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .6557116{col 30}{space 2} .1245093{col 41}{space 1}    5.27{col 50}{space 3}0.000{col 58}{space 4} .4116779{col 71}{space 3} .8997454
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .8251906{col 30}{space 2} .1210641{col 41}{space 1}    6.82{col 50}{space 3}0.000{col 58}{space 4} .5879094{col 71}{space 3} 1.062472
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .2425826{col 30}{space 2} .2207872{col 41}{space 1}    1.10{col 50}{space 3}0.272{col 58}{space 4}-.1901523{col 71}{space 3} .6753175
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2465461{col 30}{space 2} .0345084{col 41}{space 1}   -7.14{col 50}{space 3}0.000{col 58}{space 4}-.3141813{col 71}{space 3}-.1789109
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1274526{col 30}{space 2} .1344743{col 41}{space 1}   -0.95{col 50}{space 3}0.343{col 58}{space 4}-.3910174{col 71}{space 3} .1361123
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0625945{col 30}{space 2} .0887924{col 41}{space 1}    0.70{col 50}{space 3}0.481{col 58}{space 4}-.1114354{col 71}{space 3} .2366244
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.096447{col 30}{space 2} .3237892{col 41}{space 1}   12.65{col 50}{space 3}0.000{col 58}{space 4} 3.461832{col 71}{space 3} 4.731063
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .85077304
         {txt}sigma_e {c |} {res} 1.4781309
             {txt}rho {c |} {res} .24884599{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,952
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,977

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0223                                         {txt}min = {res}         1
{txt}     between = {res}0.3492                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.2461                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1890.61
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,977} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2360655{col 30}{space 2}   .04157{col 41}{space 1}    5.68{col 50}{space 3}0.000{col 58}{space 4} .1545899{col 71}{space 3} .3175412
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0159504{col 30}{space 2}  .009457{col 41}{space 1}    1.69{col 50}{space 3}0.092{col 58}{space 4} -.002585{col 71}{space 3} .0344858
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0786613{col 30}{space 2}  .120157{col 41}{space 1}   -0.65{col 50}{space 3}0.513{col 58}{space 4}-.3141647{col 71}{space 3}  .156842
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0014008{col 30}{space 2}  .002287{col 41}{space 1}    0.61{col 50}{space 3}0.540{col 58}{space 4}-.0030815{col 71}{space 3} .0058832
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0886349{col 30}{space 2} .0690905{col 41}{space 1}    1.28{col 50}{space 3}0.200{col 58}{space 4}  -.04678{col 71}{space 3} .2240498
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3156671{col 30}{space 2} .0526479{col 41}{space 1}    6.00{col 50}{space 3}0.000{col 58}{space 4}  .212479{col 71}{space 3} .4188551
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2393097{col 30}{space 2} .0999173{col 41}{space 1}    2.40{col 50}{space 3}0.017{col 58}{space 4} .0434755{col 71}{space 3} .4351439
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1484279{col 30}{space 2} .0831806{col 41}{space 1}    1.78{col 50}{space 3}0.074{col 58}{space 4} -.014603{col 71}{space 3} .3114588
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2239123{col 30}{space 2}   .11064{col 41}{space 1}    2.02{col 50}{space 3}0.043{col 58}{space 4} .0070619{col 71}{space 3} .4407627
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2834962{col 30}{space 2} .0890898{col 41}{space 1}    3.18{col 50}{space 3}0.001{col 58}{space 4} .1088835{col 71}{space 3} .4581089
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1693131{col 30}{space 2}  .072933{col 41}{space 1}   -2.32{col 50}{space 3}0.020{col 58}{space 4}-.3122592{col 71}{space 3}-.0263671
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1390691{col 30}{space 2} .0537298{col 41}{space 1}   -2.59{col 50}{space 3}0.010{col 58}{space 4}-.2443775{col 71}{space 3}-.0337606
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0015211{col 30}{space 2}  .002037{col 41}{space 1}   -0.75{col 50}{space 3}0.455{col 58}{space 4}-.0055135{col 71}{space 3} .0024713
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .033977{col 30}{space 2} .2622914{col 41}{space 1}    0.13{col 50}{space 3}0.897{col 58}{space 4}-.4801046{col 71}{space 3} .5480586
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1727118{col 30}{space 2} .1334147{col 41}{space 1}    1.29{col 50}{space 3}0.195{col 58}{space 4}-.0887763{col 71}{space 3} .4341999
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5222094{col 30}{space 2} .1081786{col 41}{space 1}    4.83{col 50}{space 3}0.000{col 58}{space 4} .3101833{col 71}{space 3} .7342354
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7402221{col 30}{space 2} .1358508{col 41}{space 1}    5.45{col 50}{space 3}0.000{col 58}{space 4} .4739595{col 71}{space 3} 1.006485
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2906356{col 30}{space 2} .1200896{col 41}{space 1}    2.42{col 50}{space 3}0.016{col 58}{space 4} .0552642{col 71}{space 3} .5260069
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .6598331{col 30}{space 2} .0945422{col 41}{space 1}    6.98{col 50}{space 3}0.000{col 58}{space 4} .4745339{col 71}{space 3} .8451324
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .1754466{col 30}{space 2} .4392118{col 41}{space 1}    0.40{col 50}{space 3}0.690{col 58}{space 4}-.6853927{col 71}{space 3} 1.036286
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2958909{col 30}{space 2} .0445796{col 41}{space 1}   -6.64{col 50}{space 3}0.000{col 58}{space 4}-.3832652{col 71}{space 3}-.2085166
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0248312{col 30}{space 2} .1327623{col 41}{space 1}   -0.19{col 50}{space 3}0.852{col 58}{space 4}-.2850405{col 71}{space 3} .2353781
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.016188{col 30}{space 2} .2210469{col 41}{space 1}   18.17{col 50}{space 3}0.000{col 58}{space 4} 3.582944{col 71}{space 3} 4.449432
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .71686036
         {txt}sigma_e {c |} {res}  1.503233
             {txt}rho {c |} {res} .18527873{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,770
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,203

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0291                                         {txt}min = {res}         3
{txt}     between = {res}0.5367                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.3483                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1626.77
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,203} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2856284{col 30}{space 2} .2118449{col 41}{space 1}    1.35{col 50}{space 3}0.178{col 58}{space 4}-.1295801{col 71}{space 3} .7008368
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0936172{col 30}{space 2} .0660443{col 41}{space 1}    1.42{col 50}{space 3}0.156{col 58}{space 4}-.0358273{col 71}{space 3} .2230616
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0440313{col 30}{space 2} .1107059{col 41}{space 1}   -0.40{col 50}{space 3}0.691{col 58}{space 4}-.2610109{col 71}{space 3} .1729482
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0257262{col 30}{space 2} .0166001{col 41}{space 1}    1.55{col 50}{space 3}0.121{col 58}{space 4}-.0068094{col 71}{space 3} .0582618
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0580122{col 30}{space 2} .0834375{col 41}{space 1}    0.70{col 50}{space 3}0.487{col 58}{space 4}-.1055222{col 71}{space 3} .2215466
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1458985{col 30}{space 2} .0684726{col 41}{space 1}    2.13{col 50}{space 3}0.033{col 58}{space 4} .0116947{col 71}{space 3} .2801023
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1920504{col 30}{space 2} .0825516{col 41}{space 1}    2.33{col 50}{space 3}0.020{col 58}{space 4} .0302522{col 71}{space 3} .3538486
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0766769{col 30}{space 2} .1378963{col 41}{space 1}    0.56{col 50}{space 3}0.578{col 58}{space 4} -.193595{col 71}{space 3} .3469488
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.1149117{col 30}{space 2} .2588707{col 41}{space 1}   -0.44{col 50}{space 3}0.657{col 58}{space 4} -.622289{col 71}{space 3} .3924656
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1755274{col 30}{space 2} .1020295{col 41}{space 1}    1.72{col 50}{space 3}0.085{col 58}{space 4}-.0244468{col 71}{space 3} .3755015
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3918602{col 30}{space 2} .0998905{col 41}{space 1}    3.92{col 50}{space 3}0.000{col 58}{space 4} .1960784{col 71}{space 3}  .587642
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}  .039142{col 30}{space 2} .1103529{col 41}{space 1}    0.35{col 50}{space 3}0.723{col 58}{space 4}-.1771457{col 71}{space 3} .2554297
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} -.048152{col 30}{space 2} .0173789{col 41}{space 1}   -2.77{col 50}{space 3}0.006{col 58}{space 4} -.082214{col 71}{space 3}  -.01409
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .5536387{col 30}{space 2}  .335011{col 41}{space 1}    1.65{col 50}{space 3}0.098{col 58}{space 4}-.1029709{col 71}{space 3} 1.210248
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.3204069{col 30}{space 2} .1174023{col 41}{space 1}   -2.73{col 50}{space 3}0.006{col 58}{space 4}-.5505112{col 71}{space 3}-.0903027
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} 1.012803{col 30}{space 2} .1437485{col 41}{space 1}    7.05{col 50}{space 3}0.000{col 58}{space 4} .7310608{col 71}{space 3} 1.294544
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.085667{col 30}{space 2} .1361351{col 41}{space 1}    7.97{col 50}{space 3}0.000{col 58}{space 4} .8188473{col 71}{space 3} 1.352487
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4014766{col 30}{space 2} .1410502{col 41}{space 1}    2.85{col 50}{space 3}0.004{col 58}{space 4} .1250232{col 71}{space 3}   .67793
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1783648{col 30}{space 2} .1142631{col 41}{space 1}    1.56{col 50}{space 3}0.119{col 58}{space 4}-.0455869{col 71}{space 3} .4023164
{txt}{space 13}imr {c |}{col 18}{res}{space 2} 2.921826{col 30}{space 2} 2.206296{col 41}{space 1}    1.32{col 50}{space 3}0.185{col 58}{space 4}-1.402434{col 71}{space 3} 7.246087
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1410391{col 30}{space 2} .0423756{col 41}{space 1}   -3.33{col 50}{space 3}0.001{col 58}{space 4}-.2240937{col 71}{space 3}-.0579844
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.4551446{col 30}{space 2} .1525402{col 41}{space 1}   -2.98{col 50}{space 3}0.003{col 58}{space 4}-.7541179{col 71}{space 3}-.1561713
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.4786537{col 30}{space 2} .1547052{col 41}{space 1}   -3.09{col 50}{space 3}0.002{col 58}{space 4}-.7818704{col 71}{space 3}-.1754371
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} -.095746{col 30}{space 2} .0667221{col 41}{space 1}   -1.43{col 50}{space 3}0.151{col 58}{space 4}-.2265188{col 71}{space 3} .0350269
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-2.195397{col 30}{space 2} 4.216416{col 41}{space 1}   -0.52{col 50}{space 3}0.603{col 58}{space 4}-10.45942{col 71}{space 3} 6.068627
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .81769933
         {txt}sigma_e {c |} {res} 1.3855139
             {txt}rho {c |} {res} .25833061{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     1,582
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}       317

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0280                                         {txt}min = {res}         4
{txt}     between = {res}0.6136                                         {txt}avg = {res}       5.0
{txt}     overall = {res}0.4180                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}   615.66
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:317} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}-.1550092{col 30}{space 2}  .462045{col 41}{space 1}   -0.34{col 50}{space 3}0.737{col 58}{space 4}-1.060601{col 71}{space 3} .7505824
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.1004208{col 30}{space 2} .1441323{col 41}{space 1}   -0.70{col 50}{space 3}0.486{col 58}{space 4}-.3829149{col 71}{space 3} .1820733
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0657993{col 30}{space 2} .2372709{col 41}{space 1}   -0.28{col 50}{space 3}0.782{col 58}{space 4}-.5308418{col 71}{space 3} .3992432
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0238677{col 30}{space 2} .0352609{col 41}{space 1}   -0.68{col 50}{space 3}0.498{col 58}{space 4}-.0929778{col 71}{space 3} .0452423
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2267069{col 30}{space 2} .1476817{col 41}{space 1}    1.54{col 50}{space 3}0.125{col 58}{space 4} -.062744{col 71}{space 3} .5161578
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1180226{col 30}{space 2} .1631008{col 41}{space 1}    0.72{col 50}{space 3}0.469{col 58}{space 4}-.2016492{col 71}{space 3} .4376943
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0277523{col 30}{space 2} .1996225{col 41}{space 1}   -0.14{col 50}{space 3}0.889{col 58}{space 4}-.4190051{col 71}{space 3} .3635005
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .268348{col 30}{space 2} .2881669{col 41}{space 1}    0.93{col 50}{space 3}0.352{col 58}{space 4}-.2964488{col 71}{space 3} .8331448
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3401701{col 30}{space 2}  .541459{col 41}{space 1}    0.63{col 50}{space 3}0.530{col 58}{space 4}-.7210701{col 71}{space 3}  1.40141
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1276135{col 30}{space 2} .1334834{col 41}{space 1}    0.96{col 50}{space 3}0.339{col 58}{space 4}-.1340092{col 71}{space 3} .3892362
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3383711{col 30}{space 2}  .191113{col 41}{space 1}    1.77{col 50}{space 3}0.077{col 58}{space 4}-.0362035{col 71}{space 3} .7129457
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1389122{col 30}{space 2} .1509606{col 41}{space 1}   -0.92{col 50}{space 3}0.357{col 58}{space 4}-.4347895{col 71}{space 3} .1569651
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} -.003278{col 30}{space 2} .0247765{col 41}{space 1}   -0.13{col 50}{space 3}0.895{col 58}{space 4} -.051839{col 71}{space 3}  .045283
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.3645901{col 30}{space 2} .7066143{col 41}{space 1}   -0.52{col 50}{space 3}0.606{col 58}{space 4}-1.749529{col 71}{space 3} 1.020348
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .5707348{col 30}{space 2} .3592781{col 41}{space 1}    1.59{col 50}{space 3}0.112{col 58}{space 4}-.1334374{col 71}{space 3} 1.274907
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} 1.594564{col 30}{space 2} .2766511{col 41}{space 1}    5.76{col 50}{space 3}0.000{col 58}{space 4} 1.052338{col 71}{space 3}  2.13679
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.215812{col 30}{space 2} .2810756{col 41}{space 1}    4.33{col 50}{space 3}0.000{col 58}{space 4} .6649139{col 71}{space 3}  1.76671
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0939992{col 30}{space 2}  .221525{col 41}{space 1}   -0.42{col 50}{space 3}0.671{col 58}{space 4}-.5281802{col 71}{space 3} .3401818
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1204274{col 30}{space 2} .2388268{col 41}{space 1}    0.50{col 50}{space 3}0.614{col 58}{space 4}-.3476645{col 71}{space 3} .5885193
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-1.589282{col 30}{space 2} 4.262922{col 41}{space 1}   -0.37{col 50}{space 3}0.709{col 58}{space 4}-9.944455{col 71}{space 3}  6.76589
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.3193407{col 30}{space 2} .0621649{col 41}{space 1}   -5.14{col 50}{space 3}0.000{col 58}{space 4}-.4411816{col 71}{space 3}-.1974997
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.3302664{col 30}{space 2} .5614084{col 41}{space 1}   -0.59{col 50}{space 3}0.556{col 58}{space 4}-1.430607{col 71}{space 3} .7700737
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.1002952{col 30}{space 2} .2683364{col 41}{space 1}   -0.37{col 50}{space 3}0.709{col 58}{space 4}-.6262249{col 71}{space 3} .4256345
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.0135621{col 30}{space 2} .4492337{col 41}{space 1}   -0.03{col 50}{space 3}0.976{col 58}{space 4}-.8940441{col 71}{space 3} .8669198
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 8.675633{col 30}{space 2}  11.9902{col 41}{space 1}    0.72{col 50}{space 3}0.469{col 58}{space 4}-14.82473{col 71}{space 3}   32.176
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .9088876
         {txt}sigma_e {c |} {res} 1.3723481
             {txt}rho {c |} {res} .30489103{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,801
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,115

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0668                                         {txt}min = {res}         6
{txt}     between = {res}0.4643                                         {txt}avg = {res}       7.0
{txt}     overall = {res}0.2822                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}  1606.23
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,115} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} -.376009{col 30}{space 2} .0829816{col 41}{space 1}   -4.53{col 50}{space 3}0.000{col 58}{space 4}  -.53865{col 71}{space 3} -.213368
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.1122929{col 30}{space 2} .0265232{col 41}{space 1}   -4.23{col 50}{space 3}0.000{col 58}{space 4}-.1642774{col 71}{space 3}-.0603083
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0318118{col 30}{space 2} .1008322{col 41}{space 1}   -0.32{col 50}{space 3}0.752{col 58}{space 4}-.2294393{col 71}{space 3} .1658156
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0320315{col 30}{space 2} .0070918{col 41}{space 1}   -4.52{col 50}{space 3}0.000{col 58}{space 4}-.0459311{col 71}{space 3}-.0181319
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0807607{col 30}{space 2} .0644507{col 41}{space 1}    1.25{col 50}{space 3}0.210{col 58}{space 4}-.0455604{col 71}{space 3} .2070817
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1309229{col 30}{space 2} .0578965{col 41}{space 1}    2.26{col 50}{space 3}0.024{col 58}{space 4} .0174479{col 71}{space 3} .2443979
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1224839{col 30}{space 2} .0838458{col 41}{space 1}    1.46{col 50}{space 3}0.144{col 58}{space 4}-.0418509{col 71}{space 3} .2868187
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .5053891{col 30}{space 2} .0623772{col 41}{space 1}    8.10{col 50}{space 3}0.000{col 58}{space 4}  .383132{col 71}{space 3} .6276461
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .8088555{col 30}{space 2} .0948783{col 41}{space 1}    8.53{col 50}{space 3}0.000{col 58}{space 4} .6228974{col 71}{space 3} .9948135
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2882751{col 30}{space 2} .0481863{col 41}{space 1}    5.98{col 50}{space 3}0.000{col 58}{space 4} .1938318{col 71}{space 3} .3827185
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1590946{col 30}{space 2} .0542607{col 41}{space 1}    2.93{col 50}{space 3}0.003{col 58}{space 4} .0527456{col 71}{space 3} .2654436
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0161938{col 30}{space 2}   .04194{col 41}{space 1}    0.39{col 50}{space 3}0.699{col 58}{space 4}-.0660072{col 71}{space 3} .0983948
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0181544{col 30}{space 2} .0046645{col 41}{space 1}    3.89{col 50}{space 3}0.000{col 58}{space 4} .0090122{col 71}{space 3} .0272967
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.7085615{col 30}{space 2} .1334766{col 41}{space 1}   -5.31{col 50}{space 3}0.000{col 58}{space 4}-.9701708{col 71}{space 3}-.4469523
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1813431{col 30}{space 2} .1789288{col 41}{space 1}    1.01{col 50}{space 3}0.311{col 58}{space 4} -.169351{col 71}{space 3} .5320372
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3945894{col 30}{space 2} .1324362{col 41}{space 1}    2.98{col 50}{space 3}0.003{col 58}{space 4} .1350193{col 71}{space 3} .6541595
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7380648{col 30}{space 2} .1652656{col 41}{space 1}    4.47{col 50}{space 3}0.000{col 58}{space 4} .4141502{col 71}{space 3} 1.061979
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .5283637{col 30}{space 2} .1283301{col 41}{space 1}    4.12{col 50}{space 3}0.000{col 58}{space 4} .2768413{col 71}{space 3} .7798862
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .6922328{col 30}{space 2} .1128484{col 41}{space 1}    6.13{col 50}{space 3}0.000{col 58}{space 4} .4710539{col 71}{space 3} .9134117
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-4.079103{col 30}{space 2} .9452194{col 41}{space 1}   -4.32{col 50}{space 3}0.000{col 58}{space 4}-5.931699{col 71}{space 3}-2.226507
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.3296236{col 30}{space 2} .0325829{col 41}{space 1}  -10.12{col 50}{space 3}0.000{col 58}{space 4}-.3934849{col 71}{space 3}-.2657623
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.6400734{col 30}{space 2} .1179621{col 41}{space 1}   -5.43{col 50}{space 3}0.000{col 58}{space 4}-.8712749{col 71}{space 3}-.4088719
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.1068978{col 30}{space 2} .0530637{col 41}{space 1}   -2.01{col 50}{space 3}0.044{col 58}{space 4}-.2109007{col 71}{space 3}-.0028948
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .4707175{col 30}{space 2} .0659082{col 41}{space 1}    7.14{col 50}{space 3}0.000{col 58}{space 4} .3415399{col 71}{space 3} .5998952
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .3951836{col 30}{space 2} .0840702{col 41}{space 1}    4.70{col 50}{space 3}0.000{col 58}{space 4} .2304089{col 71}{space 3} .5599582
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .3522583{col 30}{space 2} .0638899{col 41}{space 1}    5.51{col 50}{space 3}0.000{col 58}{space 4} .2270364{col 71}{space 3} .4774803
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 10.53694{col 30}{space 2} 1.673468{col 41}{space 1}    6.30{col 50}{space 3}0.000{col 58}{space 4} 7.257004{col 71}{space 3} 13.81688
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .88882968
         {txt}sigma_e {c |} {res} 1.4093285
             {txt}rho {c |} {res} .28456563{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. 
. esttab using  S14_balance_imr.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean _cons)
{res}{txt}(note: file S14_balance_imr.rtf not found)
(output written to {browse  `"S14_balance_imr.rtf"'})

{com}. restore
{txt}
{com}. 
. 
. ********************************************************************************
. *                                 S15-S18                                      *
. ********************************************************************************
. preserve
{txt}
{com}. drop if sum_vill<=1|sum_vill==.
{txt}(4,340 observations deleted)

{com}. 
. drop pdd9_mean no_species_mean hhsize_mean dependent_share_mean head_age_mean female_head_mean head_read_mean motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean weather_shock_mean plot_area_mean other_crop_mean
{txt}
{com}. egen pdd9_mean=mean(pdd9), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_vill=mean(pdd9_vill), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_town=mean(pdd9_town), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_dist=mean(pdd9_dist), by(HHID_panel)
{txt}
{com}. 
. foreach x of varlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. 
. 
. *                                  hh_level                                    *
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9   $xlist  pdd9_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    30,867
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     9,851

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0386                                         {txt}min = {res}         1
{txt}     between = {res}0.4815                                         {txt}avg = {res}       3.1
{txt}     overall = {res}0.3295                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 11249.63
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:9,851} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}  .060451{col 30}{space 2} .0089875{col 41}{space 1}    6.73{col 50}{space 3}0.000{col 58}{space 4} .0428359{col 71}{space 3} .0780661
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0058719{col 30}{space 2}  .004038{col 41}{space 1}   -1.45{col 50}{space 3}0.146{col 58}{space 4}-.0137863{col 71}{space 3} .0020424
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0298047{col 30}{space 2} .0407041{col 41}{space 1}   -0.73{col 50}{space 3}0.464{col 58}{space 4}-.1095834{col 71}{space 3} .0499739
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0024995{col 30}{space 2} .0007984{col 41}{space 1}   -3.13{col 50}{space 3}0.002{col 58}{space 4}-.0040644{col 71}{space 3}-.0009347
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0098415{col 30}{space 2}   .02521{col 41}{space 1}    0.39{col 50}{space 3}0.696{col 58}{space 4}-.0395692{col 71}{space 3} .0592523
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2614414{col 30}{space 2} .0209163{col 41}{space 1}   12.50{col 50}{space 3}0.000{col 58}{space 4} .2204462{col 71}{space 3} .3024367
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1264169{col 30}{space 2} .0430936{col 41}{space 1}    2.93{col 50}{space 3}0.003{col 58}{space 4}  .041955{col 71}{space 3} .2108788
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1707383{col 30}{space 2} .0255665{col 41}{space 1}    6.68{col 50}{space 3}0.000{col 58}{space 4} .1206289{col 71}{space 3} .2208477
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1635672{col 30}{space 2} .0312537{col 41}{space 1}    5.23{col 50}{space 3}0.000{col 58}{space 4}  .102311{col 71}{space 3} .2248234
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .122022{col 30}{space 2}  .028783{col 41}{space 1}    4.24{col 50}{space 3}0.000{col 58}{space 4} .0656084{col 71}{space 3} .1784357
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1551004{col 30}{space 2} .0245605{col 41}{space 1}    6.32{col 50}{space 3}0.000{col 58}{space 4} .1069627{col 71}{space 3} .2032382
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.110542{col 30}{space 2} .0191156{col 41}{space 1}   -5.78{col 50}{space 3}0.000{col 58}{space 4}-.1480079{col 71}{space 3}-.0730762
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0006927{col 30}{space 2} .0013815{col 41}{space 1}    0.50{col 50}{space 3}0.616{col 58}{space 4} -.002015{col 71}{space 3} .0034005
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0783861{col 30}{space 2} .0238091{col 41}{space 1}    3.29{col 50}{space 3}0.001{col 58}{space 4} .0317211{col 71}{space 3} .1250512
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0601701{col 30}{space 2} .0645459{col 41}{space 1}    0.93{col 50}{space 3}0.351{col 58}{space 4}-.0663376{col 71}{space 3} .1866777
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5377014{col 30}{space 2} .0406819{col 41}{space 1}   13.22{col 50}{space 3}0.000{col 58}{space 4} .4579663{col 71}{space 3} .6174365
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7227872{col 30}{space 2} .0481112{col 41}{space 1}   15.02{col 50}{space 3}0.000{col 58}{space 4}  .628491{col 71}{space 3} .8170833
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3751699{col 30}{space 2} .0494374{col 41}{space 1}    7.59{col 50}{space 3}0.000{col 58}{space 4} .2782744{col 71}{space 3} .4720654
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2248094{col 30}{space 2} .0378232{col 41}{space 1}    5.94{col 50}{space 3}0.000{col 58}{space 4} .1506774{col 71}{space 3} .2989415
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.3785871{col 30}{space 2} .0797153{col 41}{space 1}   -4.75{col 50}{space 3}0.000{col 58}{space 4}-.5348263{col 71}{space 3}-.2223479
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0233781{col 30}{space 2} .0116052{col 41}{space 1}    2.01{col 50}{space 3}0.044{col 58}{space 4} .0006324{col 71}{space 3} .0461238
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.1686337{col 30}{space 2} .0794689{col 41}{space 1}   -2.12{col 50}{space 3}0.034{col 58}{space 4}-.3243899{col 71}{space 3}-.0128774
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.513037{col 30}{space 2} .0412255{col 41}{space 1}  -36.70{col 50}{space 3}0.000{col 58}{space 4}-1.593838{col 71}{space 3}-1.432237
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.3283065{col 30}{space 2} .0630335{col 41}{space 1}   -5.21{col 50}{space 3}0.000{col 58}{space 4}  -.45185{col 71}{space 3} -.204763
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2} .2363898{col 30}{space 2}  .143679{col 41}{space 1}    1.65{col 50}{space 3}0.100{col 58}{space 4}-.0452158{col 71}{space 3} .5179955
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .3920803{col 30}{space 2} .0500066{col 41}{space 1}    7.84{col 50}{space 3}0.000{col 58}{space 4} .2940692{col 71}{space 3} .4900914
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.1177465{col 30}{space 2} .1012659{col 41}{space 1}   -1.16{col 50}{space 3}0.245{col 58}{space 4}-.3162239{col 71}{space 3}  .080731
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0517405{col 30}{space 2} .0912038{col 41}{space 1}    0.57{col 50}{space 3}0.571{col 58}{space 4}-.1270157{col 71}{space 3} .2304967
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}  .110174{col 30}{space 2} .0920328{col 41}{space 1}    1.20{col 50}{space 3}0.231{col 58}{space 4} -.070207{col 71}{space 3}  .290555
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .1413495{col 30}{space 2} .0952547{col 41}{space 1}    1.48{col 50}{space 3}0.138{col 58}{space 4}-.0453462{col 71}{space 3} .3280452
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1716129{col 30}{space 2} .0946272{col 41}{space 1}    1.81{col 50}{space 3}0.070{col 58}{space 4}-.0138529{col 71}{space 3} .3570787
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.1922923{col 30}{space 2} .0952603{col 41}{space 1}   -2.02{col 50}{space 3}0.044{col 58}{space 4}-.3789991{col 71}{space 3}-.0055855
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .3189699{col 30}{space 2} .0942129{col 41}{space 1}    3.39{col 50}{space 3}0.001{col 58}{space 4} .1343161{col 71}{space 3} .5036237
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.0148061{col 30}{space 2} .1073445{col 41}{space 1}   -0.14{col 50}{space 3}0.890{col 58}{space 4}-.2251975{col 71}{space 3} .1955852
{txt}{space 11}2018  {c |}{col 18}{res}{space 2}  .603449{col 30}{space 2} .0966214{col 41}{space 1}    6.25{col 50}{space 3}0.000{col 58}{space 4} .4140744{col 71}{space 3} .7928235
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .2753901{col 30}{space 2} .0983448{col 41}{space 1}    2.80{col 50}{space 3}0.005{col 58}{space 4} .0826378{col 71}{space 3} .4681425
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.742419{col 30}{space 2} .1208684{col 41}{space 1}   39.24{col 50}{space 3}0.000{col 58}{space 4} 4.505522{col 71}{space 3} 4.979317
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .71263125
         {txt}sigma_e {c |} {res} 1.2162388
             {txt}rho {c |} {res} .25557262{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,299
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,149

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0295                                         {txt}min = {res}         1
{txt}     between = {res}0.3114                                         {txt}avg = {res}       3.0
{txt}     overall = {res}0.1994                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1629.10
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,149} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1006148{col 30}{space 2} .0126412{col 41}{space 1}    7.96{col 50}{space 3}0.000{col 58}{space 4} .0758386{col 71}{space 3} .1253911
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0522336{col 30}{space 2} .0084313{col 41}{space 1}    6.20{col 50}{space 3}0.000{col 58}{space 4} .0357085{col 71}{space 3} .0687586
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0009717{col 30}{space 2} .0646492{col 41}{space 1}   -0.02{col 50}{space 3}0.988{col 58}{space 4}-.1276817{col 71}{space 3} .1257384
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0013864{col 30}{space 2} .0012408{col 41}{space 1}    1.12{col 50}{space 3}0.264{col 58}{space 4}-.0010455{col 71}{space 3} .0038183
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0159754{col 30}{space 2} .0410708{col 41}{space 1}    0.39{col 50}{space 3}0.697{col 58}{space 4}-.0645218{col 71}{space 3} .0964726
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3102931{col 30}{space 2} .0334219{col 41}{space 1}    9.28{col 50}{space 3}0.000{col 58}{space 4} .2447875{col 71}{space 3} .3757988
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.1963749{col 30}{space 2} .1607389{col 41}{space 1}   -1.22{col 50}{space 3}0.222{col 58}{space 4}-.5114174{col 71}{space 3} .1186676
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1004211{col 30}{space 2} .0411024{col 41}{space 1}    2.44{col 50}{space 3}0.015{col 58}{space 4} .0198619{col 71}{space 3} .1809803
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0663585{col 30}{space 2} .0524127{col 41}{space 1}   -1.27{col 50}{space 3}0.205{col 58}{space 4}-.1690855{col 71}{space 3} .0363685
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0452356{col 30}{space 2}  .072331{col 41}{space 1}    0.63{col 50}{space 3}0.532{col 58}{space 4}-.0965306{col 71}{space 3} .1870017
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2314278{col 30}{space 2} .0519312{col 41}{space 1}    4.46{col 50}{space 3}0.000{col 58}{space 4} .1296446{col 71}{space 3}  .333211
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1684354{col 30}{space 2} .0313365{col 41}{space 1}   -5.38{col 50}{space 3}0.000{col 58}{space 4}-.2298538{col 71}{space 3}-.1070169
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0064314{col 30}{space 2} .0036505{col 41}{space 1}    1.76{col 50}{space 3}0.078{col 58}{space 4}-.0007234{col 71}{space 3} .0135862
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3088416{col 30}{space 2} .0340509{col 41}{space 1}    9.07{col 50}{space 3}0.000{col 58}{space 4} .2421032{col 71}{space 3} .3755801
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} 1.151063{col 30}{space 2}  .302253{col 41}{space 1}    3.81{col 50}{space 3}0.000{col 58}{space 4} .5586584{col 71}{space 3} 1.743468
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .428957{col 30}{space 2} .0623256{col 41}{space 1}    6.88{col 50}{space 3}0.000{col 58}{space 4} .3068011{col 71}{space 3}  .551113
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5063037{col 30}{space 2} .0767227{col 41}{space 1}    6.60{col 50}{space 3}0.000{col 58}{space 4}   .35593{col 71}{space 3} .6566774
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .5048123{col 30}{space 2} .1359063{col 41}{space 1}    3.71{col 50}{space 3}0.000{col 58}{space 4} .2384407{col 71}{space 3} .7711838
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .126949{col 30}{space 2} .0688087{col 41}{space 1}    1.84{col 50}{space 3}0.065{col 58}{space 4}-.0079136{col 71}{space 3} .2618117
{txt}{space 13}imr {c |}{col 18}{res}{space 2} 1.361698{col 30}{space 2} .1712575{col 41}{space 1}    7.95{col 50}{space 3}0.000{col 58}{space 4}  1.02604{col 71}{space 3} 1.697357
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .1145135{col 30}{space 2} .0168846{col 41}{space 1}    6.78{col 50}{space 3}0.000{col 58}{space 4} .0814203{col 71}{space 3} .1476068
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.4205306{col 30}{space 2}   .03576{col 41}{space 1}  -11.76{col 50}{space 3}0.000{col 58}{space 4} -.490619{col 71}{space 3}-.3504423
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}   1.9715{col 30}{space 2} .1573454{col 41}{space 1}   12.53{col 50}{space 3}0.000{col 58}{space 4} 1.663109{col 71}{space 3} 2.279892
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .66040639
         {txt}sigma_e {c |} {res} 1.0615607
             {txt}rho {c |} {res} .27902959{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,301
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,381

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0348                                         {txt}min = {res}         1
{txt}     between = {res}0.4115                                         {txt}avg = {res}       3.1
{txt}     overall = {res}0.2807                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1432.46
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,381} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1577475{col 30}{space 2}  .022325{col 41}{space 1}    7.07{col 50}{space 3}0.000{col 58}{space 4} .1139913{col 71}{space 3} .2015036
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0083494{col 30}{space 2} .0124088{col 41}{space 1}    0.67{col 50}{space 3}0.501{col 58}{space 4}-.0159713{col 71}{space 3} .0326702
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2781283{col 30}{space 2} .1071975{col 41}{space 1}   -2.59{col 50}{space 3}0.009{col 58}{space 4}-.4882316{col 71}{space 3}-.0680251
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0011204{col 30}{space 2} .0020291{col 41}{space 1}    0.55{col 50}{space 3}0.581{col 58}{space 4}-.0028566{col 71}{space 3} .0050974
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1244058{col 30}{space 2} .0623281{col 41}{space 1}   -2.00{col 50}{space 3}0.046{col 58}{space 4}-.2465666{col 71}{space 3}-.0022449
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2933748{col 30}{space 2} .0598435{col 41}{space 1}    4.90{col 50}{space 3}0.000{col 58}{space 4} .1760837{col 71}{space 3} .4106659
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2428793{col 30}{space 2} .1997751{col 41}{space 1}    1.22{col 50}{space 3}0.224{col 58}{space 4}-.1486727{col 71}{space 3} .6344314
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0511209{col 30}{space 2} .0703651{col 41}{space 1}    0.73{col 50}{space 3}0.468{col 58}{space 4}-.0867922{col 71}{space 3}  .189034
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0513767{col 30}{space 2} .1433247{col 41}{space 1}    0.36{col 50}{space 3}0.720{col 58}{space 4}-.2295345{col 71}{space 3}  .332288
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1331653{col 30}{space 2} .0828336{col 41}{space 1}    1.61{col 50}{space 3}0.108{col 58}{space 4}-.0291856{col 71}{space 3} .2955163
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2299609{col 30}{space 2} .0573929{col 41}{space 1}    4.01{col 50}{space 3}0.000{col 58}{space 4} .1174729{col 71}{space 3}  .342449
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1376623{col 30}{space 2} .0474561{col 41}{space 1}   -2.90{col 50}{space 3}0.004{col 58}{space 4}-.2306745{col 71}{space 3}-.0446502
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0248571{col 30}{space 2} .0355472{col 41}{space 1}    0.70{col 50}{space 3}0.484{col 58}{space 4}-.0448141{col 71}{space 3} .0945284
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0945022{col 30}{space 2} .0655395{col 41}{space 1}    1.44{col 50}{space 3}0.149{col 58}{space 4}-.0339528{col 71}{space 3} .2229573
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0541978{col 30}{space 2} .3287907{col 41}{space 1}   -0.16{col 50}{space 3}0.869{col 58}{space 4}-.6986157{col 71}{space 3} .5902201
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7703012{col 30}{space 2}  .112081{col 41}{space 1}    6.87{col 50}{space 3}0.000{col 58}{space 4} .5506265{col 71}{space 3} .9899759
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.118461{col 30}{space 2} .1837231{col 41}{space 1}    6.09{col 50}{space 3}0.000{col 58}{space 4} .7583708{col 71}{space 3} 1.478552
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4988061{col 30}{space 2} .1196464{col 41}{space 1}    4.17{col 50}{space 3}0.000{col 58}{space 4} .2643036{col 71}{space 3} .7333087
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3690628{col 30}{space 2} .1044775{col 41}{space 1}    3.53{col 50}{space 3}0.000{col 58}{space 4} .1642907{col 71}{space 3} .5738349
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .7864466{col 30}{space 2} .2421999{col 41}{space 1}    3.25{col 50}{space 3}0.001{col 58}{space 4} .3117435{col 71}{space 3}  1.26115
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0028588{col 30}{space 2} .0302326{col 41}{space 1}    0.09{col 50}{space 3}0.925{col 58}{space 4}-.0563959{col 71}{space 3} .0621135
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .6518651{col 30}{space 2} .1428348{col 41}{space 1}    4.56{col 50}{space 3}0.000{col 58}{space 4}  .371914{col 71}{space 3} .9318161
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3500116{col 30}{space 2} .0958569{col 41}{space 1}    3.65{col 50}{space 3}0.000{col 58}{space 4} .1621356{col 71}{space 3} .5378876
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.878731{col 30}{space 2} .3173395{col 41}{space 1}   12.22{col 50}{space 3}0.000{col 58}{space 4} 3.256757{col 71}{space 3} 4.500705
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .68015831
         {txt}sigma_e {c |} {res} 1.2826925
             {txt}rho {c |} {res} .21946578{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,552
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,853

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0435                                         {txt}min = {res}         1
{txt}     between = {res}0.2582                                         {txt}avg = {res}       1.9
{txt}     overall = {res}0.1782                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1119.21
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,853} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2049799{col 30}{space 2} .0391492{col 41}{space 1}    5.24{col 50}{space 3}0.000{col 58}{space 4} .1282489{col 71}{space 3}  .281711
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0034959{col 30}{space 2} .0088729{col 41}{space 1}   -0.39{col 50}{space 3}0.694{col 58}{space 4}-.0208865{col 71}{space 3} .0138947
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1030752{col 30}{space 2} .1120412{col 41}{space 1}   -0.92{col 50}{space 3}0.358{col 58}{space 4}-.3226719{col 71}{space 3} .1165215
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0006089{col 30}{space 2} .0021201{col 41}{space 1}   -0.29{col 50}{space 3}0.774{col 58}{space 4}-.0047642{col 71}{space 3} .0035465
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0840111{col 30}{space 2} .0647234{col 41}{space 1}    1.30{col 50}{space 3}0.194{col 58}{space 4}-.0428444{col 71}{space 3} .2108665
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2853584{col 30}{space 2} .0495278{col 41}{space 1}    5.76{col 50}{space 3}0.000{col 58}{space 4} .1882857{col 71}{space 3} .3824311
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2887248{col 30}{space 2} .1102712{col 41}{space 1}    2.62{col 50}{space 3}0.009{col 58}{space 4} .0725972{col 71}{space 3} .5048524
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1304487{col 30}{space 2} .0792073{col 41}{space 1}    1.65{col 50}{space 3}0.100{col 58}{space 4}-.0247948{col 71}{space 3} .2856921
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3404689{col 30}{space 2}  .124964{col 41}{space 1}    2.72{col 50}{space 3}0.006{col 58}{space 4}  .095544{col 71}{space 3} .5853938
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1927815{col 30}{space 2} .0897677{col 41}{space 1}    2.15{col 50}{space 3}0.032{col 58}{space 4} .0168401{col 71}{space 3} .3687228
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1949482{col 30}{space 2} .0690589{col 41}{space 1}   -2.82{col 50}{space 3}0.005{col 58}{space 4}-.3303012{col 71}{space 3}-.0595951
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1467157{col 30}{space 2} .0487695{col 41}{space 1}   -3.01{col 50}{space 3}0.003{col 58}{space 4}-.2423021{col 71}{space 3}-.0511292
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0004213{col 30}{space 2} .0019411{col 41}{space 1}    0.22{col 50}{space 3}0.828{col 58}{space 4}-.0033833{col 71}{space 3} .0042258
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0749211{col 30}{space 2} .2374115{col 41}{space 1}    0.32{col 50}{space 3}0.752{col 58}{space 4} -.390397{col 71}{space 3} .5402392
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1106796{col 30}{space 2}  .138799{col 41}{space 1}    0.80{col 50}{space 3}0.425{col 58}{space 4}-.1613614{col 71}{space 3} .3827205
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4005969{col 30}{space 2} .1009021{col 41}{space 1}    3.97{col 50}{space 3}0.000{col 58}{space 4} .2028324{col 71}{space 3} .5983613
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4475602{col 30}{space 2} .1450123{col 41}{space 1}    3.09{col 50}{space 3}0.002{col 58}{space 4} .1633413{col 71}{space 3}  .731779
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}   .26472{col 30}{space 2} .1171792{col 41}{space 1}    2.26{col 50}{space 3}0.024{col 58}{space 4}  .035053{col 71}{space 3}  .494387
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .5270666{col 30}{space 2} .0885213{col 41}{space 1}    5.95{col 50}{space 3}0.000{col 58}{space 4} .3535681{col 71}{space 3} .7005651
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-1.020902{col 30}{space 2} .4351227{col 41}{space 1}   -2.35{col 50}{space 3}0.019{col 58}{space 4}-1.873727{col 71}{space 3}-.1680768
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2325294{col 30}{space 2} .0413014{col 41}{space 1}   -5.63{col 50}{space 3}0.000{col 58}{space 4}-.3134786{col 71}{space 3}-.1515801
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .5500558{col 30}{space 2} .1249293{col 41}{space 1}    4.40{col 50}{space 3}0.000{col 58}{space 4}  .305199{col 71}{space 3} .7949127
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.865346{col 30}{space 2}  .219194{col 41}{space 1}   22.20{col 50}{space 3}0.000{col 58}{space 4} 4.435733{col 71}{space 3} 5.294958
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .56178731
         {txt}sigma_e {c |} {res}  1.393923
             {txt}rho {c |} {res} .13973315{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,014
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,108

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0664                                         {txt}min = {res}         1
{txt}     between = {res}0.3893                                         {txt}avg = {res}       3.6
{txt}     overall = {res}0.2401                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}   900.21
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,108} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}  .499084{col 30}{space 2} .2006408{col 41}{space 1}    2.49{col 50}{space 3}0.013{col 58}{space 4} .1058352{col 71}{space 3} .8923327
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .1332637{col 30}{space 2} .0616061{col 41}{space 1}    2.16{col 50}{space 3}0.031{col 58}{space 4} .0125179{col 71}{space 3} .2540095
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0619151{col 30}{space 2} .1064426{col 41}{space 1}    0.58{col 50}{space 3}0.561{col 58}{space 4}-.1467086{col 71}{space 3} .2705388
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0404707{col 30}{space 2} .0154493{col 41}{space 1}    2.62{col 50}{space 3}0.009{col 58}{space 4} .0101906{col 71}{space 3} .0707509
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1503308{col 30}{space 2} .0763122{col 41}{space 1}    1.97{col 50}{space 3}0.049{col 58}{space 4} .0007616{col 71}{space 3}    .2999
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1450017{col 30}{space 2} .0615436{col 41}{space 1}    2.36{col 50}{space 3}0.018{col 58}{space 4} .0243785{col 71}{space 3} .2656249
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1376557{col 30}{space 2} .0794542{col 41}{space 1}    1.73{col 50}{space 3}0.083{col 58}{space 4}-.0180716{col 71}{space 3}  .293383
{txt}{space 11}phone {c |}{col 18}{res}{space 2} -.048694{col 30}{space 2} .1288912{col 41}{space 1}   -0.38{col 50}{space 3}0.706{col 58}{space 4}-.3013161{col 71}{space 3} .2039281
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} -.404215{col 30}{space 2} .2499615{col 41}{space 1}   -1.62{col 50}{space 3}0.106{col 58}{space 4}-.8941306{col 71}{space 3} .0857006
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1762065{col 30}{space 2} .1057309{col 41}{space 1}    1.67{col 50}{space 3}0.096{col 58}{space 4}-.0310222{col 71}{space 3} .3834352
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .4541448{col 30}{space 2} .0933395{col 41}{space 1}    4.87{col 50}{space 3}0.000{col 58}{space 4} .2712028{col 71}{space 3} .6370868
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .1335715{col 30}{space 2} .1002726{col 41}{space 1}    1.33{col 50}{space 3}0.183{col 58}{space 4}-.0629592{col 71}{space 3} .3301022
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0246946{col 30}{space 2} .0153899{col 41}{space 1}   -1.60{col 50}{space 3}0.109{col 58}{space 4}-.0548583{col 71}{space 3} .0054692
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .8174628{col 30}{space 2}  .319713{col 41}{space 1}    2.56{col 50}{space 3}0.011{col 58}{space 4} .1908368{col 71}{space 3} 1.444089
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0768061{col 30}{space 2} .1142046{col 41}{space 1}   -0.67{col 50}{space 3}0.501{col 58}{space 4}-.3006429{col 71}{space 3} .1470307
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .9700595{col 30}{space 2} .1293815{col 41}{space 1}    7.50{col 50}{space 3}0.000{col 58}{space 4} .7164764{col 71}{space 3} 1.223643
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8189432{col 30}{space 2} .1238698{col 41}{space 1}    6.61{col 50}{space 3}0.000{col 58}{space 4} .5761629{col 71}{space 3} 1.061723
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0489424{col 30}{space 2} .1458324{col 41}{space 1}    0.34{col 50}{space 3}0.737{col 58}{space 4}-.2368839{col 71}{space 3} .3347686
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0497679{col 30}{space 2} .1075089{col 41}{space 1}   -0.46{col 50}{space 3}0.643{col 58}{space 4}-.2604816{col 71}{space 3} .1609457
{txt}{space 13}imr {c |}{col 18}{res}{space 2} 4.684083{col 30}{space 2} 2.098288{col 41}{space 1}    2.23{col 50}{space 3}0.026{col 58}{space 4} .5715147{col 71}{space 3} 8.796652
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0323449{col 30}{space 2} .0422045{col 41}{space 1}   -0.77{col 50}{space 3}0.443{col 58}{space 4}-.1150642{col 71}{space 3} .0503743
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.8717688{col 30}{space 2} .1433176{col 41}{space 1}   -6.08{col 50}{space 3}0.000{col 58}{space 4}-1.152666{col 71}{space 3}-.5908714
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.7711034{col 30}{space 2}  .145158{col 41}{space 1}   -5.31{col 50}{space 3}0.000{col 58}{space 4}-1.055608{col 71}{space 3} -.486599
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.4477548{col 30}{space 2} .0633475{col 41}{space 1}   -7.07{col 50}{space 3}0.000{col 58}{space 4}-.5719136{col 71}{space 3}-.3235959
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-4.548464{col 30}{space 2} 3.978993{col 41}{space 1}   -1.14{col 50}{space 3}0.253{col 58}{space 4}-12.34715{col 71}{space 3} 3.250219
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .70936422
         {txt}sigma_e {c |} {res} 1.2397811
             {txt}rho {c |} {res} .24663468{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     1,113
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}       271

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0639                                         {txt}min = {res}         1
{txt}     between = {res}0.3894                                         {txt}avg = {res}       4.1
{txt}     overall = {res}0.2687                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}   304.02
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:271} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0559432{col 30}{space 2} .4299029{col 41}{space 1}    0.13{col 50}{space 3}0.896{col 58}{space 4} -.786651{col 71}{space 3} .8985375
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} -.089735{col 30}{space 2}  .131047{col 41}{space 1}   -0.68{col 50}{space 3}0.493{col 58}{space 4}-.3465824{col 71}{space 3} .1671124
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .3322235{col 30}{space 2} .2167748{col 41}{space 1}    1.53{col 50}{space 3}0.125{col 58}{space 4}-.0926472{col 71}{space 3} .7570943
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0173035{col 30}{space 2} .0320362{col 41}{space 1}   -0.54{col 50}{space 3}0.589{col 58}{space 4}-.0800934{col 71}{space 3} .0454864
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3544607{col 30}{space 2} .1321353{col 41}{space 1}    2.68{col 50}{space 3}0.007{col 58}{space 4} .0954803{col 71}{space 3}  .613441
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1255782{col 30}{space 2}   .15582{col 41}{space 1}    0.81{col 50}{space 3}0.420{col 58}{space 4}-.1798232{col 71}{space 3} .4309797
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2043558{col 30}{space 2} .2005108{col 41}{space 1}    1.02{col 50}{space 3}0.308{col 58}{space 4}-.1886382{col 71}{space 3} .5973498
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3020542{col 30}{space 2} .2693848{col 41}{space 1}    1.12{col 50}{space 3}0.262{col 58}{space 4}-.2259304{col 71}{space 3} .8300388
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1330314{col 30}{space 2}  .485167{col 41}{space 1}    0.27{col 50}{space 3}0.784{col 58}{space 4}-.8178784{col 71}{space 3} 1.083941
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0861784{col 30}{space 2} .1274043{col 41}{space 1}    0.68{col 50}{space 3}0.499{col 58}{space 4}-.1635295{col 71}{space 3} .3358863
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2081187{col 30}{space 2} .1798058{col 41}{space 1}    1.16{col 50}{space 3}0.247{col 58}{space 4}-.1442941{col 71}{space 3} .5605315
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.2282947{col 30}{space 2} .1460088{col 41}{space 1}   -1.56{col 50}{space 3}0.118{col 58}{space 4}-.5144667{col 71}{space 3} .0578772
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}   .00278{col 30}{space 2} .0223973{col 41}{space 1}    0.12{col 50}{space 3}0.901{col 58}{space 4}-.0411179{col 71}{space 3} .0466778
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.1907931{col 30}{space 2} .6496986{col 41}{space 1}   -0.29{col 50}{space 3}0.769{col 58}{space 4}-1.464179{col 71}{space 3} 1.082593
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .7127059{col 30}{space 2} .3306314{col 41}{space 1}    2.16{col 50}{space 3}0.031{col 58}{space 4} .0646803{col 71}{space 3} 1.360732
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}   .72973{col 30}{space 2} .2400179{col 41}{space 1}    3.04{col 50}{space 3}0.002{col 58}{space 4} .2593036{col 71}{space 3} 1.200157
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.186287{col 30}{space 2} .2424743{col 41}{space 1}    4.89{col 50}{space 3}0.000{col 58}{space 4}  .711046{col 71}{space 3} 1.661528
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} -.132494{col 30}{space 2} .2091382{col 41}{space 1}   -0.63{col 50}{space 3}0.526{col 58}{space 4}-.5423974{col 71}{space 3} .2774093
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1840654{col 30}{space 2} .2220985{col 41}{space 1}    0.83{col 50}{space 3}0.407{col 58}{space 4}-.2512396{col 71}{space 3} .6193703
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-1.271499{col 30}{space 2}  3.95832{col 41}{space 1}   -0.32{col 50}{space 3}0.748{col 58}{space 4}-9.029664{col 71}{space 3} 6.486665
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0396545{col 30}{space 2} .0577072{col 41}{space 1}   -0.69{col 50}{space 3}0.492{col 58}{space 4}-.1527585{col 71}{space 3} .0734495
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.2175941{col 30}{space 2} .5118453{col 41}{space 1}   -0.43{col 50}{space 3}0.671{col 58}{space 4}-1.220792{col 71}{space 3} .7856043
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0137278{col 30}{space 2} .2532634{col 41}{space 1}    0.05{col 50}{space 3}0.957{col 58}{space 4}-.4826593{col 71}{space 3} .5101148
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0070138{col 30}{space 2} .4119066{col 41}{space 1}    0.02{col 50}{space 3}0.986{col 58}{space 4}-.8003083{col 71}{space 3} .8143359
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 7.963828{col 30}{space 2}  11.0768{col 41}{space 1}    0.72{col 50}{space 3}0.472{col 58}{space 4} -13.7463{col 71}{space 3} 29.67395
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .78201261
         {txt}sigma_e {c |} {res}  1.139127
             {txt}rho {c |} {res} .32032183{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     6,588
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,089

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0789                                         {txt}min = {res}         1
{txt}     between = {res}0.2887                                         {txt}avg = {res}       6.0
{txt}     overall = {res}0.1814                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}   927.02
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,089} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}-.2123595{col 30}{space 2} .0783507{col 41}{space 1}   -2.71{col 50}{space 3}0.007{col 58}{space 4} -.365924{col 71}{space 3}-.0587949
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0993206{col 30}{space 2} .0247617{col 41}{space 1}   -4.01{col 50}{space 3}0.000{col 58}{space 4}-.1478525{col 71}{space 3}-.0507887
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1123473{col 30}{space 2} .0915062{col 41}{space 1}    1.23{col 50}{space 3}0.220{col 58}{space 4}-.0670017{col 71}{space 3} .2916962
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0251628{col 30}{space 2} .0065379{col 41}{space 1}   -3.85{col 50}{space 3}0.000{col 58}{space 4}-.0379769{col 71}{space 3}-.0123487
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0141201{col 30}{space 2} .0564845{col 41}{space 1}    0.25{col 50}{space 3}0.803{col 58}{space 4}-.0965875{col 71}{space 3} .1248276
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2283868{col 30}{space 2} .0541236{col 41}{space 1}    4.22{col 50}{space 3}0.000{col 58}{space 4} .1223065{col 71}{space 3} .3344671
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1068145{col 30}{space 2} .0765276{col 41}{space 1}    1.40{col 50}{space 3}0.163{col 58}{space 4}-.0431768{col 71}{space 3} .2568057
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .4384526{col 30}{space 2} .0635052{col 41}{space 1}    6.90{col 50}{space 3}0.000{col 58}{space 4} .3139846{col 71}{space 3} .5629206
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .6445422{col 30}{space 2} .0855226{col 41}{space 1}    7.54{col 50}{space 3}0.000{col 58}{space 4}  .476921{col 71}{space 3} .8121635
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1069043{col 30}{space 2} .0455581{col 41}{space 1}    2.35{col 50}{space 3}0.019{col 58}{space 4} .0176121{col 71}{space 3} .1961965
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0898787{col 30}{space 2} .0498053{col 41}{space 1}    1.80{col 50}{space 3}0.071{col 58}{space 4}-.0077379{col 71}{space 3} .1874953
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0601253{col 30}{space 2} .0380414{col 41}{space 1}   -1.58{col 50}{space 3}0.114{col 58}{space 4}-.1346852{col 71}{space 3} .0144345
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}  .016566{col 30}{space 2} .0041073{col 41}{space 1}    4.03{col 50}{space 3}0.000{col 58}{space 4} .0085159{col 71}{space 3} .0246161
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.5068369{col 30}{space 2}  .122781{col 41}{space 1}   -4.13{col 50}{space 3}0.000{col 58}{space 4}-.7474831{col 71}{space 3}-.2661906
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1602162{col 30}{space 2} .1449413{col 41}{space 1}    1.11{col 50}{space 3}0.269{col 58}{space 4}-.1238635{col 71}{space 3} .4442959
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .306754{col 30}{space 2} .1097945{col 41}{space 1}    2.79{col 50}{space 3}0.005{col 58}{space 4} .0915607{col 71}{space 3} .5219473
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6375371{col 30}{space 2} .1421669{col 41}{space 1}    4.48{col 50}{space 3}0.000{col 58}{space 4} .3588951{col 71}{space 3} .9161791
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .157943{col 30}{space 2} .1007686{col 41}{space 1}    1.57{col 50}{space 3}0.117{col 58}{space 4}-.0395597{col 71}{space 3} .3554458
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2990519{col 30}{space 2} .0933169{col 41}{space 1}    3.20{col 50}{space 3}0.001{col 58}{space 4} .1161542{col 71}{space 3} .4819496
{txt}{space 13}imr {c |}{col 18}{res}{space 2} -3.66058{col 30}{space 2} .9023038{col 41}{space 1}   -4.06{col 50}{space 3}0.000{col 58}{space 4}-5.429062{col 71}{space 3}-1.892097
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} -.000566{col 30}{space 2}  .031856{col 41}{space 1}   -0.02{col 50}{space 3}0.986{col 58}{space 4}-.0630027{col 71}{space 3} .0618707
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5356891{col 30}{space 2} .1158477{col 41}{space 1}   -4.62{col 50}{space 3}0.000{col 58}{space 4}-.7627465{col 71}{space 3}-.3086317
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.1044429{col 30}{space 2} .0495475{col 41}{space 1}   -2.11{col 50}{space 3}0.035{col 58}{space 4}-.2015542{col 71}{space 3}-.0073315
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}  .502243{col 30}{space 2} .0618159{col 41}{space 1}    8.12{col 50}{space 3}0.000{col 58}{space 4}  .381086{col 71}{space 3}    .6234
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .3787948{col 30}{space 2}  .075915{col 41}{space 1}    4.99{col 50}{space 3}0.000{col 58}{space 4} .2300041{col 71}{space 3} .5275854
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .4792524{col 30}{space 2} .0578655{col 41}{space 1}    8.28{col 50}{space 3}0.000{col 58}{space 4} .3658381{col 71}{space 3} .5926668
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 10.33527{col 30}{space 2} 1.581251{col 41}{space 1}    6.54{col 50}{space 3}0.000{col 58}{space 4} 7.236073{col 71}{space 3} 13.43446
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .68775193
         {txt}sigma_e {c |} {res} 1.2167017
             {txt}rho {c |} {res} .24214755{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. 
. 
. esttab using  S15_balance_imr.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean _cons )
{res}{txt}(note: file S15_balance_imr.rtf not found)
(output written to {browse  `"S15_balance_imr.rtf"'})

{com}. 
. 
. 
. 
. 
. *                          vill_village_level                                  *
. 
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill i.country i.year   , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    30,867
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     9,851

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0366                                         {txt}min = {res}         1
{txt}     between = {res}0.4935                                         {txt}avg = {res}       3.1
{txt}     overall = {res}0.3363                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}37{txt})     =  {res} 11650.06
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:9,851} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0458345{col 30}{space 2} .0095486{col 41}{space 1}    4.80{col 50}{space 3}0.000{col 58}{space 4} .0271195{col 71}{space 3} .0645494
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0497226{col 30}{space 2} .0034608{col 41}{space 1}  -14.37{col 50}{space 3}0.000{col 58}{space 4}-.0565056{col 71}{space 3}-.0429397
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0064997{col 30}{space 2} .0039889{col 41}{space 1}   -1.63{col 50}{space 3}0.103{col 58}{space 4}-.0143179{col 71}{space 3} .0013184
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0333373{col 30}{space 2} .0404592{col 41}{space 1}   -0.82{col 50}{space 3}0.410{col 58}{space 4}-.1126358{col 71}{space 3} .0459612
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0048106{col 30}{space 2} .0007719{col 41}{space 1}   -6.23{col 50}{space 3}0.000{col 58}{space 4}-.0063235{col 71}{space 3}-.0032976
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0179718{col 30}{space 2}  .025038{col 41}{space 1}   -0.72{col 50}{space 3}0.473{col 58}{space 4}-.0670453{col 71}{space 3} .0311017
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2506256{col 30}{space 2} .0208387{col 41}{space 1}   12.03{col 50}{space 3}0.000{col 58}{space 4} .2097825{col 71}{space 3} .2914687
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1182295{col 30}{space 2} .0429733{col 41}{space 1}    2.75{col 50}{space 3}0.006{col 58}{space 4} .0340034{col 71}{space 3} .2024556
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1849327{col 30}{space 2}  .025529{col 41}{space 1}    7.24{col 50}{space 3}0.000{col 58}{space 4} .1348968{col 71}{space 3} .2349686
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1809397{col 30}{space 2}  .031164{col 41}{space 1}    5.81{col 50}{space 3}0.000{col 58}{space 4} .1198593{col 71}{space 3}   .24202
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1255118{col 30}{space 2} .0287887{col 41}{space 1}    4.36{col 50}{space 3}0.000{col 58}{space 4}  .069087{col 71}{space 3} .1819365
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1474263{col 30}{space 2} .0245704{col 41}{space 1}    6.00{col 50}{space 3}0.000{col 58}{space 4} .0992693{col 71}{space 3} .1955834
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0931602{col 30}{space 2} .0191434{col 41}{space 1}   -4.87{col 50}{space 3}0.000{col 58}{space 4}-.1306807{col 71}{space 3}-.0556398
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0025235{col 30}{space 2} .0013605{col 41}{space 1}    1.85{col 50}{space 3}0.064{col 58}{space 4}-.0001431{col 71}{space 3}   .00519
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0405725{col 30}{space 2} .0238623{col 41}{space 1}    1.70{col 50}{space 3}0.089{col 58}{space 4}-.0061967{col 71}{space 3} .0873417
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .033535{col 30}{space 2} .0636838{col 41}{space 1}    0.53{col 50}{space 3}0.598{col 58}{space 4}-.0912828{col 71}{space 3} .1583529
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4900604{col 30}{space 2} .0406172{col 41}{space 1}   12.07{col 50}{space 3}0.000{col 58}{space 4} .4104522{col 71}{space 3} .5696686
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6156084{col 30}{space 2}  .048042{col 41}{space 1}   12.81{col 50}{space 3}0.000{col 58}{space 4} .5214478{col 71}{space 3}  .709769
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2667146{col 30}{space 2} .0493114{col 41}{space 1}    5.41{col 50}{space 3}0.000{col 58}{space 4}  .170066{col 71}{space 3} .3633632
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1762679{col 30}{space 2} .0374623{col 41}{space 1}    4.71{col 50}{space 3}0.000{col 58}{space 4} .1028431{col 71}{space 3} .2496927
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.7768302{col 30}{space 2} .0648071{col 41}{space 1}  -11.99{col 50}{space 3}0.000{col 58}{space 4}-.9038497{col 71}{space 3}-.6498106
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .0750773{col 30}{space 2} .0128421{col 41}{space 1}    5.85{col 50}{space 3}0.000{col 58}{space 4} .0499072{col 71}{space 3} .1002475
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2} -.086259{col 30}{space 2} .0717458{col 41}{space 1}   -1.20{col 50}{space 3}0.229{col 58}{space 4}-.2268782{col 71}{space 3} .0543601
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2} -1.81913{col 30}{space 2} .0459589{col 41}{space 1}  -39.58{col 50}{space 3}0.000{col 58}{space 4}-1.909207{col 71}{space 3}-1.729052
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.4179738{col 30}{space 2} .0596222{col 41}{space 1}   -7.01{col 50}{space 3}0.000{col 58}{space 4}-.5348311{col 71}{space 3}-.3011165
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2} .4294317{col 30}{space 2} .1235122{col 41}{space 1}    3.48{col 50}{space 3}0.001{col 58}{space 4} .1873523{col 71}{space 3} .6715111
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .1452364{col 30}{space 2} .0523411{col 41}{space 1}    2.77{col 50}{space 3}0.006{col 58}{space 4} .0426497{col 71}{space 3} .2478231
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.0064374{col 30}{space 2} .1008109{col 41}{space 1}   -0.06{col 50}{space 3}0.949{col 58}{space 4}-.2040232{col 71}{space 3} .1911483
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .1737795{col 30}{space 2} .0914149{col 41}{space 1}    1.90{col 50}{space 3}0.057{col 58}{space 4}-.0053905{col 71}{space 3} .3529495
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .1861396{col 30}{space 2}  .092024{col 41}{space 1}    2.02{col 50}{space 3}0.043{col 58}{space 4} .0057759{col 71}{space 3} .3665033
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .2711647{col 30}{space 2} .0950939{col 41}{space 1}    2.85{col 50}{space 3}0.004{col 58}{space 4} .0847841{col 71}{space 3} .4575452
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .3221397{col 30}{space 2} .0938704{col 41}{space 1}    3.43{col 50}{space 3}0.001{col 58}{space 4} .1381571{col 71}{space 3} .5061224
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.2383437{col 30}{space 2} .0948263{col 41}{space 1}   -2.51{col 50}{space 3}0.012{col 58}{space 4}-.4241998{col 71}{space 3}-.0524876
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .4636961{col 30}{space 2} .0937781{col 41}{space 1}    4.94{col 50}{space 3}0.000{col 58}{space 4} .2798945{col 71}{space 3} .6474977
{txt}{space 11}2016  {c |}{col 18}{res}{space 2} .1401053{col 30}{space 2} .1060228{col 41}{space 1}    1.32{col 50}{space 3}0.186{col 58}{space 4}-.0676956{col 71}{space 3} .3479061
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .7327578{col 30}{space 2} .0963768{col 41}{space 1}    7.60{col 50}{space 3}0.000{col 58}{space 4} .5438628{col 71}{space 3} .9216528
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .4395478{col 30}{space 2} .0969193{col 41}{space 1}    4.54{col 50}{space 3}0.000{col 58}{space 4} .2495894{col 71}{space 3} .6295062
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2}  5.32049{col 30}{space 2} .1259066{col 41}{space 1}   42.26{col 50}{space 3}0.000{col 58}{space 4} 5.073718{col 71}{space 3} 5.567263
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .70041696
         {txt}sigma_e {c |} {res} 1.2169466
             {txt}rho {c |} {res} .24883246{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,299
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,149

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0235                                         {txt}min = {res}         1
{txt}     between = {res}0.3167                                         {txt}avg = {res}       3.0
{txt}     overall = {res}0.2004                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1694.25
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,149} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0521214{col 30}{space 2} .0158142{col 41}{space 1}    3.30{col 50}{space 3}0.001{col 58}{space 4} .0211261{col 71}{space 3} .0831168
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0257515{col 30}{space 2} .0101619{col 41}{space 1}   -2.53{col 50}{space 3}0.011{col 58}{space 4}-.0456686{col 71}{space 3}-.0058345
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0589345{col 30}{space 2} .0083838{col 41}{space 1}    7.03{col 50}{space 3}0.000{col 58}{space 4} .0425026{col 71}{space 3} .0753665
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.050176{col 30}{space 2} .0646845{col 41}{space 1}   -0.78{col 50}{space 3}0.438{col 58}{space 4}-.1769554{col 71}{space 3} .0766033
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0016883{col 30}{space 2} .0012031{col 41}{space 1}   -1.40{col 50}{space 3}0.161{col 58}{space 4}-.0040462{col 71}{space 3} .0006697
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0359149{col 30}{space 2} .0410917{col 41}{space 1}   -0.87{col 50}{space 3}0.382{col 58}{space 4}-.1164531{col 71}{space 3} .0446233
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3054084{col 30}{space 2} .0335199{col 41}{space 1}    9.11{col 50}{space 3}0.000{col 58}{space 4} .2397106{col 71}{space 3} .3711062
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2317865{col 30}{space 2} .1587984{col 41}{space 1}   -1.46{col 50}{space 3}0.144{col 58}{space 4}-.5430255{col 71}{space 3} .0794526
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1797564{col 30}{space 2} .0401627{col 41}{space 1}    4.48{col 50}{space 3}0.000{col 58}{space 4}  .101039{col 71}{space 3} .2584738
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0947885{col 30}{space 2} .0501754{col 41}{space 1}    1.89{col 50}{space 3}0.059{col 58}{space 4}-.0035536{col 71}{space 3} .1931305
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0601085{col 30}{space 2} .0720044{col 41}{space 1}    0.83{col 50}{space 3}0.404{col 58}{space 4}-.0810176{col 71}{space 3} .2012345
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2001229{col 30}{space 2} .0522802{col 41}{space 1}    3.83{col 50}{space 3}0.000{col 58}{space 4} .0976556{col 71}{space 3} .3025903
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1180114{col 30}{space 2} .0313981{col 41}{space 1}   -3.76{col 50}{space 3}0.000{col 58}{space 4}-.1795505{col 71}{space 3}-.0564724
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0147536{col 30}{space 2} .0039211{col 41}{space 1}    3.76{col 50}{space 3}0.000{col 58}{space 4} .0070684{col 71}{space 3} .0224388
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2262379{col 30}{space 2}  .035241{col 41}{space 1}    6.42{col 50}{space 3}0.000{col 58}{space 4} .1571667{col 71}{space 3}  .295309
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} 1.046155{col 30}{space 2} .2925806{col 41}{space 1}    3.58{col 50}{space 3}0.000{col 58}{space 4} .4727077{col 71}{space 3} 1.619603
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4158864{col 30}{space 2} .0620325{col 41}{space 1}    6.70{col 50}{space 3}0.000{col 58}{space 4} .2943049{col 71}{space 3} .5374679
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3476526{col 30}{space 2} .0761426{col 41}{space 1}    4.57{col 50}{space 3}0.000{col 58}{space 4} .1984158{col 71}{space 3} .4968893
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4883596{col 30}{space 2}  .131657{col 41}{space 1}    3.71{col 50}{space 3}0.000{col 58}{space 4} .2303167{col 71}{space 3} .7464026
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1004899{col 30}{space 2} .0690552{col 41}{space 1}    1.46{col 50}{space 3}0.146{col 58}{space 4}-.0348558{col 71}{space 3} .2358357
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .2639177{col 30}{space 2} .1331065{col 41}{space 1}    1.98{col 50}{space 3}0.047{col 58}{space 4} .0030337{col 71}{space 3} .5248018
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .1432162{col 30}{space 2} .0203326{col 41}{space 1}    7.04{col 50}{space 3}0.000{col 58}{space 4}  .103365{col 71}{space 3} .1830673
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.2252856{col 30}{space 2} .0305982{col 41}{space 1}   -7.36{col 50}{space 3}0.000{col 58}{space 4} -.285257{col 71}{space 3}-.1653142
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.295295{col 30}{space 2} .1776692{col 41}{space 1}   12.92{col 50}{space 3}0.000{col 58}{space 4}  1.94707{col 71}{space 3}  2.64352
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .65649753
         {txt}sigma_e {c |} {res} 1.0652599
             {txt}rho {c |} {res} .27525731{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_MALAWI  if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,301
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,381

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0196                                         {txt}min = {res}         1
{txt}     between = {res}0.4111                                         {txt}avg = {res}       3.1
{txt}     overall = {res}0.2773                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1406.12
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,381} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0721927{col 30}{space 2} .0264269{col 41}{space 1}    2.73{col 50}{space 3}0.006{col 58}{space 4}  .020397{col 71}{space 3} .1239884
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2} -.038552{col 30}{space 2} .0107799{col 41}{space 1}   -3.58{col 50}{space 3}0.000{col 58}{space 4}-.0596802{col 71}{space 3}-.0174239
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0063942{col 30}{space 2} .0124468{col 41}{space 1}   -0.51{col 50}{space 3}0.607{col 58}{space 4}-.0307894{col 71}{space 3} .0180011
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2656879{col 30}{space 2} .1065974{col 41}{space 1}   -2.49{col 50}{space 3}0.013{col 58}{space 4} -.474615{col 71}{space 3}-.0567608
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0037123{col 30}{space 2} .0020125{col 41}{space 1}   -1.84{col 50}{space 3}0.065{col 58}{space 4}-.0076568{col 71}{space 3} .0002323
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} -.101676{col 30}{space 2} .0625525{col 41}{space 1}   -1.63{col 50}{space 3}0.104{col 58}{space 4}-.2242766{col 71}{space 3} .0209247
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3039065{col 30}{space 2} .0603207{col 41}{space 1}    5.04{col 50}{space 3}0.000{col 58}{space 4} .1856801{col 71}{space 3} .4221328
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1992316{col 30}{space 2} .1969144{col 41}{space 1}    1.01{col 50}{space 3}0.312{col 58}{space 4}-.1867135{col 71}{space 3} .5851767
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0855053{col 30}{space 2} .0715067{col 41}{space 1}    1.20{col 50}{space 3}0.232{col 58}{space 4}-.0546452{col 71}{space 3} .2256558
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1801865{col 30}{space 2} .1456647{col 41}{space 1}    1.24{col 50}{space 3}0.216{col 58}{space 4}-.1053111{col 71}{space 3} .4656842
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1384865{col 30}{space 2} .0835088{col 41}{space 1}    1.66{col 50}{space 3}0.097{col 58}{space 4}-.0251879{col 71}{space 3} .3021608
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2213093{col 30}{space 2} .0575993{col 41}{space 1}    3.84{col 50}{space 3}0.000{col 58}{space 4} .1084167{col 71}{space 3} .3342018
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1828239{col 30}{space 2}  .046986{col 41}{space 1}   -3.89{col 50}{space 3}0.000{col 58}{space 4}-.2749147{col 71}{space 3}-.0907331
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0986605{col 30}{space 2} .0391368{col 41}{space 1}    2.52{col 50}{space 3}0.012{col 58}{space 4} .0219538{col 71}{space 3} .1753672
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0391651{col 30}{space 2} .0654309{col 41}{space 1}    0.60{col 50}{space 3}0.549{col 58}{space 4}-.0890772{col 71}{space 3} .1674074
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .110459{col 30}{space 2} .3414324{col 41}{space 1}    0.32{col 50}{space 3}0.746{col 58}{space 4}-.5587361{col 71}{space 3} .7796541
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7259483{col 30}{space 2} .1137019{col 41}{space 1}    6.38{col 50}{space 3}0.000{col 58}{space 4} .5030967{col 71}{space 3} .9487999
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8478061{col 30}{space 2} .1860303{col 41}{space 1}    4.56{col 50}{space 3}0.000{col 58}{space 4} .4831936{col 71}{space 3} 1.212419
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3308602{col 30}{space 2} .1212283{col 41}{space 1}    2.73{col 50}{space 3}0.006{col 58}{space 4}  .093257{col 71}{space 3} .5684633
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .263336{col 30}{space 2} .1047507{col 41}{space 1}    2.51{col 50}{space 3}0.012{col 58}{space 4} .0580284{col 71}{space 3} .4686435
{txt}{space 13}imr {c |}{col 18}{res}{space 2} -.486428{col 30}{space 2}  .203707{col 41}{space 1}   -2.39{col 50}{space 3}0.017{col 58}{space 4}-.8856864{col 71}{space 3}-.0871696
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0577505{col 30}{space 2} .0416706{col 41}{space 1}   -1.39{col 50}{space 3}0.166{col 58}{space 4}-.1394233{col 71}{space 3} .0239224
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .0617706{col 30}{space 2} .1209529{col 41}{space 1}    0.51{col 50}{space 3}0.610{col 58}{space 4}-.1752926{col 71}{space 3} .2988338
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.0411349{col 30}{space 2} .0861678{col 41}{space 1}   -0.48{col 50}{space 3}0.633{col 58}{space 4}-.2100207{col 71}{space 3} .1277509
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.921243{col 30}{space 2} .3375665{col 41}{space 1}   17.54{col 50}{space 3}0.000{col 58}{space 4} 5.259625{col 71}{space 3} 6.582861
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .67102666
         {txt}sigma_e {c |} {res} 1.2905168
             {txt}rho {c |} {res} .21282534{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,552
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,853

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0353                                         {txt}min = {res}         1
{txt}     between = {res}0.2858                                         {txt}avg = {res}       1.9
{txt}     overall = {res}0.1927                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1243.57
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,853} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0960831{col 30}{space 2} .0307971{col 41}{space 1}    3.12{col 50}{space 3}0.002{col 58}{space 4} .0357218{col 71}{space 3} .1564443
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0698052{col 30}{space 2} .0070459{col 41}{space 1}   -9.91{col 50}{space 3}0.000{col 58}{space 4} -.083615{col 71}{space 3}-.0559954
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} -.017487{col 30}{space 2} .0085688{col 41}{space 1}   -2.04{col 50}{space 3}0.041{col 58}{space 4}-.0342815{col 71}{space 3}-.0006926
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0695365{col 30}{space 2} .1108509{col 41}{space 1}   -0.63{col 50}{space 3}0.530{col 58}{space 4}-.2868003{col 71}{space 3} .1477272
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0064556{col 30}{space 2} .0019321{col 41}{space 1}   -3.34{col 50}{space 3}0.001{col 58}{space 4}-.0102424{col 71}{space 3}-.0026689
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0635921{col 30}{space 2} .0637311{col 41}{space 1}    1.00{col 50}{space 3}0.318{col 58}{space 4}-.0613185{col 71}{space 3} .1885027
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2634925{col 30}{space 2} .0490664{col 41}{space 1}    5.37{col 50}{space 3}0.000{col 58}{space 4} .1673241{col 71}{space 3}  .359661
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2785098{col 30}{space 2} .1106623{col 41}{space 1}    2.52{col 50}{space 3}0.012{col 58}{space 4} .0616157{col 71}{space 3} .4954038
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1737724{col 30}{space 2} .0793248{col 41}{space 1}    2.19{col 50}{space 3}0.028{col 58}{space 4} .0182987{col 71}{space 3} .3292461
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3155282{col 30}{space 2} .1264003{col 41}{space 1}    2.50{col 50}{space 3}0.013{col 58}{space 4} .0677881{col 71}{space 3} .5632682
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1984247{col 30}{space 2} .0898205{col 41}{space 1}    2.21{col 50}{space 3}0.027{col 58}{space 4} .0223798{col 71}{space 3} .3744695
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.2125694{col 30}{space 2} .0696449{col 41}{space 1}   -3.05{col 50}{space 3}0.002{col 58}{space 4}-.3490709{col 71}{space 3}-.0760678
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1196589{col 30}{space 2} .0487813{col 41}{space 1}   -2.45{col 50}{space 3}0.014{col 58}{space 4}-.2152684{col 71}{space 3}-.0240494
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0027378{col 30}{space 2} .0018108{col 41}{space 1}    1.51{col 50}{space 3}0.131{col 58}{space 4}-.0008113{col 71}{space 3}  .006287
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0981979{col 30}{space 2} .2407472{col 41}{space 1}    0.41{col 50}{space 3}0.683{col 58}{space 4} -.373658{col 71}{space 3} .5700538
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0949074{col 30}{space 2} .1384779{col 41}{space 1}    0.69{col 50}{space 3}0.493{col 58}{space 4}-.1765043{col 71}{space 3} .3663191
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1973231{col 30}{space 2} .1027246{col 41}{space 1}    1.92{col 50}{space 3}0.055{col 58}{space 4}-.0040134{col 71}{space 3} .3986595
{txt}electricity_mean {c |}{col 18}{res}{space 2} .2843201{col 30}{space 2} .1490615{col 41}{space 1}    1.91{col 50}{space 3}0.056{col 58}{space 4} -.007835{col 71}{space 3} .5764752
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1210579{col 30}{space 2}  .117285{col 41}{space 1}    1.03{col 50}{space 3}0.302{col 58}{space 4}-.1088165{col 71}{space 3} .3509323
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4258953{col 30}{space 2} .0894649{col 41}{space 1}    4.76{col 50}{space 3}0.000{col 58}{space 4} .2505473{col 71}{space 3} .6012432
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-2.399029{col 30}{space 2} .3443733{col 41}{space 1}   -6.97{col 50}{space 3}0.000{col 58}{space 4}-3.073989{col 71}{space 3} -1.72407
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0406965{col 30}{space 2} .0363593{col 41}{space 1}   -1.12{col 50}{space 3}0.263{col 58}{space 4}-.1119594{col 71}{space 3} .0305664
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .9584777{col 30}{space 2} .1034524{col 41}{space 1}    9.26{col 50}{space 3}0.000{col 58}{space 4} .7557147{col 71}{space 3} 1.161241
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 6.164852{col 30}{space 2} .2159437{col 41}{space 1}   28.55{col 50}{space 3}0.000{col 58}{space 4}  5.74161{col 71}{space 3} 6.588094
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .51272304
         {txt}sigma_e {c |} {res}  1.397801
             {txt}rho {c |} {res} .11859118{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,014
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,108

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0693                                         {txt}min = {res}         1
{txt}     between = {res}0.4309                                         {txt}avg = {res}       3.6
{txt}     overall = {res}0.2666                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}25{txt})     =  {res}  1052.30
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,108} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0998708{col 30}{space 2} .0264651{col 41}{space 1}    3.77{col 50}{space 3}0.000{col 58}{space 4} .0480001{col 71}{space 3} .1517415
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.1132983{col 30}{space 2}   .01435{col 41}{space 1}   -7.90{col 50}{space 3}0.000{col 58}{space 4}-.1414239{col 71}{space 3}-.0851728
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0049148{col 30}{space 2} .0110151{col 41}{space 1}   -0.45{col 50}{space 3}0.655{col 58}{space 4} -.026504{col 71}{space 3} .0166744
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0016872{col 30}{space 2} .1047426{col 41}{space 1}   -0.02{col 50}{space 3}0.987{col 58}{space 4}-.2069789{col 71}{space 3} .2036044
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0018364{col 30}{space 2} .0027399{col 41}{space 1}    0.67{col 50}{space 3}0.503{col 58}{space 4}-.0035338{col 71}{space 3} .0072066
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1093798{col 30}{space 2} .0753874{col 41}{space 1}    1.45{col 50}{space 3}0.147{col 58}{space 4}-.0383767{col 71}{space 3} .2571364
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0345938{col 30}{space 2}  .051313{col 41}{space 1}    0.67{col 50}{space 3}0.500{col 58}{space 4}-.0659779{col 71}{space 3} .1351655
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0490932{col 30}{space 2} .0697895{col 41}{space 1}    0.70{col 50}{space 3}0.482{col 58}{space 4}-.0876918{col 71}{space 3} .1858782
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1926581{col 30}{space 2} .0690084{col 41}{space 1}    2.79{col 50}{space 3}0.005{col 58}{space 4} .0574041{col 71}{space 3} .3279121
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1364323{col 30}{space 2} .0902791{col 41}{space 1}    1.51{col 50}{space 3}0.131{col 58}{space 4}-.0405115{col 71}{space 3} .3133761
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .270406{col 30}{space 2} .0939882{col 41}{space 1}    2.88{col 50}{space 3}0.004{col 58}{space 4} .0861924{col 71}{space 3} .4546196
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2794973{col 30}{space 2} .0675958{col 41}{space 1}    4.13{col 50}{space 3}0.000{col 58}{space 4} .1470119{col 71}{space 3} .4119827
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}  .049198{col 30}{space 2}  .089243{col 41}{space 1}    0.55{col 50}{space 3}0.581{col 58}{space 4}-.1257152{col 71}{space 3} .2241111
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0034269{col 30}{space 2} .0129825{col 41}{space 1}    0.26{col 50}{space 3}0.792{col 58}{space 4}-.0220184{col 71}{space 3} .0288723
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1241907{col 30}{space 2} .1263926{col 41}{space 1}    0.98{col 50}{space 3}0.326{col 58}{space 4}-.1235342{col 71}{space 3} .3719157
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0022454{col 30}{space 2} .1103966{col 41}{space 1}   -0.02{col 50}{space 3}0.984{col 58}{space 4}-.2186187{col 71}{space 3} .2141279
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .819355{col 30}{space 2} .1295122{col 41}{space 1}    6.33{col 50}{space 3}0.000{col 58}{space 4} .5655159{col 71}{space 3} 1.073194
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7225305{col 30}{space 2}  .118813{col 41}{space 1}    6.08{col 50}{space 3}0.000{col 58}{space 4} .4896612{col 71}{space 3} .9553998
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0179283{col 30}{space 2} .1429469{col 41}{space 1}    0.13{col 50}{space 3}0.900{col 58}{space 4}-.2622424{col 71}{space 3}  .298099
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.1447266{col 30}{space 2} .1034383{col 41}{space 1}   -1.40{col 50}{space 3}0.162{col 58}{space 4} -.347462{col 71}{space 3} .0580088
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.2974149{col 30}{space 2} .2288018{col 41}{space 1}   -1.30{col 50}{space 3}0.194{col 58}{space 4}-.7458582{col 71}{space 3} .1510283
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .1111686{col 30}{space 2} .0381454{col 41}{space 1}    2.91{col 50}{space 3}0.004{col 58}{space 4} .0364051{col 71}{space 3} .1859322
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5477697{col 30}{space 2} .0639549{col 41}{space 1}   -8.56{col 50}{space 3}0.000{col 58}{space 4}-.6731191{col 71}{space 3}-.4224203
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} -.483655{col 30}{space 2}   .06037{col 41}{space 1}   -8.01{col 50}{space 3}0.000{col 58}{space 4}-.6019781{col 71}{space 3}-.3653319
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3976615{col 30}{space 2} .0583622{col 41}{space 1}   -6.81{col 50}{space 3}0.000{col 58}{space 4}-.5120493{col 71}{space 3}-.2832736
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.161655{col 30}{space 2} .5162755{col 41}{space 1}   10.00{col 50}{space 3}0.000{col 58}{space 4} 4.149773{col 71}{space 3} 6.173536
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .66949565
         {txt}sigma_e {c |} {res} 1.2380765
             {txt}rho {c |} {res}  .2262551{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     1,113
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}       271

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0630                                         {txt}min = {res}         1
{txt}     between = {res}0.4004                                         {txt}avg = {res}       4.1
{txt}     overall = {res}0.2720                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}25{txt})     =  {res}   322.39
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:271} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0115419{col 30}{space 2} .0480885{col 41}{space 1}    0.24{col 50}{space 3}0.810{col 58}{space 4}-.0827098{col 71}{space 3} .1057936
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0095081{col 30}{space 2} .0186677{col 41}{space 1}   -0.51{col 50}{space 3}0.611{col 58}{space 4}-.0460961{col 71}{space 3} .0270799
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.1092743{col 30}{space 2} .0218887{col 41}{space 1}   -4.99{col 50}{space 3}0.000{col 58}{space 4}-.1521753{col 71}{space 3}-.0663734
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .3240988{col 30}{space 2} .2159257{col 41}{space 1}    1.50{col 50}{space 3}0.133{col 58}{space 4}-.0991078{col 71}{space 3} .7473055
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0211673{col 30}{space 2} .0047134{col 41}{space 1}   -4.49{col 50}{space 3}0.000{col 58}{space 4}-.0304054{col 71}{space 3}-.0119293
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3629676{col 30}{space 2} .1289163{col 41}{space 1}    2.82{col 50}{space 3}0.005{col 58}{space 4} .1102964{col 71}{space 3} .6156389
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1339234{col 30}{space 2} .1264684{col 41}{space 1}    1.06{col 50}{space 3}0.290{col 58}{space 4}-.1139502{col 71}{space 3} .3817969
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1979285{col 30}{space 2} .1776779{col 41}{space 1}    1.11{col 50}{space 3}0.265{col 58}{space 4}-.1503138{col 71}{space 3} .5461707
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3332675{col 30}{space 2}  .121946{col 41}{space 1}    2.73{col 50}{space 3}0.006{col 58}{space 4} .0942577{col 71}{space 3} .5722773
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1960195{col 30}{space 2} .1304368{col 41}{space 1}    1.50{col 50}{space 3}0.133{col 58}{space 4}-.0596319{col 71}{space 3} .4516708
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0960859{col 30}{space 2} .0932479{col 41}{space 1}    1.03{col 50}{space 3}0.303{col 58}{space 4}-.0866767{col 71}{space 3} .2788485
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1879592{col 30}{space 2} .1046503{col 41}{space 1}    1.80{col 50}{space 3}0.072{col 58}{space 4}-.0171517{col 71}{space 3} .3930701
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.2400949{col 30}{space 2} .1090482{col 41}{space 1}   -2.20{col 50}{space 3}0.028{col 58}{space 4}-.4538255{col 71}{space 3}-.0263643
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0067606{col 30}{space 2} .0136079{col 41}{space 1}    0.50{col 50}{space 3}0.619{col 58}{space 4}-.0199103{col 71}{space 3} .0334314
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  -.27789{col 30}{space 2} .1153338{col 41}{space 1}   -2.41{col 50}{space 3}0.016{col 58}{space 4}-.5039401{col 71}{space 3}-.0518399
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .764087{col 30}{space 2} .3414908{col 41}{space 1}    2.24{col 50}{space 3}0.025{col 58}{space 4} .0947774{col 71}{space 3} 1.433397
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7125078{col 30}{space 2} .2405561{col 41}{space 1}    2.96{col 50}{space 3}0.003{col 58}{space 4} .2410266{col 71}{space 3} 1.183989
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.160818{col 30}{space 2} .2456314{col 41}{space 1}    4.73{col 50}{space 3}0.000{col 58}{space 4}  .679389{col 71}{space 3} 1.642246
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1361991{col 30}{space 2} .2106139{col 41}{space 1}   -0.65{col 50}{space 3}0.518{col 58}{space 4}-.5489948{col 71}{space 3} .2765966
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .170415{col 30}{space 2}  .220355{col 41}{space 1}    0.77{col 50}{space 3}0.439{col 58}{space 4}-.2614729{col 71}{space 3} .6023029
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-1.792935{col 30}{space 2} .2784031{col 41}{space 1}   -6.44{col 50}{space 3}0.000{col 58}{space 4}-2.338595{col 71}{space 3}-1.247275
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.1001856{col 30}{space 2} .0736621{col 41}{space 1}   -1.36{col 50}{space 3}0.174{col 58}{space 4}-.2445606{col 71}{space 3} .0441894
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.2885844{col 30}{space 2} .1158121{col 41}{space 1}   -2.49{col 50}{space 3}0.013{col 58}{space 4}-.5155719{col 71}{space 3}-.0615969
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0453229{col 30}{space 2}  .091902{col 41}{space 1}    0.49{col 50}{space 3}0.622{col 58}{space 4}-.1348017{col 71}{space 3} .2254475
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.0363201{col 30}{space 2} .1048023{col 41}{space 1}   -0.35{col 50}{space 3}0.729{col 58}{space 4}-.2417288{col 71}{space 3} .1690886
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 9.814882{col 30}{space 2} .9553338{col 41}{space 1}   10.27{col 50}{space 3}0.000{col 58}{space 4} 7.942463{col 71}{space 3}  11.6873
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .76709058
         {txt}sigma_e {c |} {res} 1.1396466
             {txt}rho {c |} {res} .31179578{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     6,588
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,089

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0748                                         {txt}min = {res}         1
{txt}     between = {res}0.3084                                         {txt}avg = {res}       6.0
{txt}     overall = {res}0.1888                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}27{txt})     =  {res}   965.06
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,089} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0018202{col 30}{space 2} .0193955{col 41}{space 1}    0.09{col 50}{space 3}0.925{col 58}{space 4}-.0361942{col 71}{space 3} .0398346
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}  -.02192{col 30}{space 2} .0067787{col 41}{space 1}   -3.23{col 50}{space 3}0.001{col 58}{space 4} -.035206{col 71}{space 3}-.0086339
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0363368{col 30}{space 2} .0096953{col 41}{space 1}   -3.75{col 50}{space 3}0.000{col 58}{space 4}-.0553391{col 71}{space 3}-.0173344
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1104055{col 30}{space 2}  .091156{col 41}{space 1}    1.21{col 50}{space 3}0.226{col 58}{space 4} -.068257{col 71}{space 3}  .289068
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0088113{col 30}{space 2} .0021676{col 41}{space 1}   -4.06{col 50}{space 3}0.000{col 58}{space 4}-.0130598{col 71}{space 3}-.0045628
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0118031{col 30}{space 2} .0559197{col 41}{space 1}    0.21{col 50}{space 3}0.833{col 58}{space 4}-.0977975{col 71}{space 3} .1214037
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2526954{col 30}{space 2} .0514558{col 41}{space 1}    4.91{col 50}{space 3}0.000{col 58}{space 4} .1518438{col 71}{space 3} .3535471
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1505093{col 30}{space 2} .0751737{col 41}{space 1}    2.00{col 50}{space 3}0.045{col 58}{space 4} .0031716{col 71}{space 3} .2978471
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3475091{col 30}{space 2} .0518935{col 41}{space 1}    6.70{col 50}{space 3}0.000{col 58}{space 4} .2457997{col 71}{space 3} .4492184
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4568711{col 30}{space 2} .0536083{col 41}{space 1}    8.52{col 50}{space 3}0.000{col 58}{space 4} .3518007{col 71}{space 3} .5619414
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0555227{col 30}{space 2} .0419398{col 41}{space 1}    1.32{col 50}{space 3}0.186{col 58}{space 4}-.0266779{col 71}{space 3} .1377233
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1469414{col 30}{space 2} .0447916{col 41}{space 1}    3.28{col 50}{space 3}0.001{col 58}{space 4} .0591514{col 71}{space 3} .2347314
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0260044{col 30}{space 2} .0363549{col 41}{space 1}   -0.72{col 50}{space 3}0.474{col 58}{space 4}-.0972588{col 71}{space 3}   .04525
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0062027{col 30}{space 2} .0017085{col 41}{space 1}    3.63{col 50}{space 3}0.000{col 58}{space 4}  .002854{col 71}{space 3} .0095513
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.2162842{col 30}{space 2} .0470442{col 41}{space 1}   -4.60{col 50}{space 3}0.000{col 58}{space 4} -.308489{col 71}{space 3}-.1240793
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1326997{col 30}{space 2} .1428778{col 41}{space 1}    0.93{col 50}{space 3}0.353{col 58}{space 4}-.1473357{col 71}{space 3} .4127351
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .2480767{col 30}{space 2} .1078459{col 41}{space 1}    2.30{col 50}{space 3}0.021{col 58}{space 4} .0367026{col 71}{space 3} .4594508
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5499791{col 30}{space 2} .1364646{col 41}{space 1}    4.03{col 50}{space 3}0.000{col 58}{space 4} .2825133{col 71}{space 3} .8174449
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1562191{col 30}{space 2} .1003507{col 41}{space 1}    1.56{col 50}{space 3}0.120{col 58}{space 4}-.0404646{col 71}{space 3} .3529028
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3403415{col 30}{space 2} .0914455{col 41}{space 1}    3.72{col 50}{space 3}0.000{col 58}{space 4} .1611116{col 71}{space 3} .5195714
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-1.262662{col 30}{space 2} .1621664{col 41}{space 1}   -7.79{col 50}{space 3}0.000{col 58}{space 4}-1.580502{col 71}{space 3}-.9448217
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .1110869{col 30}{space 2} .0370721{col 41}{space 1}    3.00{col 50}{space 3}0.003{col 58}{space 4}  .038427{col 71}{space 3} .1837467
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.2625615{col 30}{space 2} .0600706{col 41}{space 1}   -4.37{col 50}{space 3}0.000{col 58}{space 4}-.3802977{col 71}{space 3}-.1448253
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.1153189{col 30}{space 2} .0502881{col 41}{space 1}   -2.29{col 50}{space 3}0.022{col 58}{space 4}-.2138818{col 71}{space 3} -.016756
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .4018474{col 30}{space 2} .0498097{col 41}{space 1}    8.07{col 50}{space 3}0.000{col 58}{space 4} .3042222{col 71}{space 3} .4994725
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .2246474{col 30}{space 2}  .050546{col 41}{space 1}    4.44{col 50}{space 3}0.000{col 58}{space 4} .1255791{col 71}{space 3} .3237157
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2}  .404565{col 30}{space 2} .0487879{col 41}{space 1}    8.29{col 50}{space 3}0.000{col 58}{space 4} .3089425{col 71}{space 3} .5001876
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.733579{col 30}{space 2} .3613186{col 41}{space 1}   15.87{col 50}{space 3}0.000{col 58}{space 4} 5.025407{col 71}{space 3}  6.44175
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69763086
         {txt}sigma_e {c |} {res} 1.2199934
             {txt}rho {c |} {res} .24641563{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S16_balance_imr.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9_vill    $xlist  pdd9_mean_vill sum_vill _cons)
{res}{txt}(note: file S16_balance_imr.rtf not found)
(output written to {browse  `"S16_balance_imr.rtf"'})

{com}. 
. 
. 
. 
. 
. 
. *                          town_village_level                                  *
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town i.country i.year   , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    30,867
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     9,851

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0387                                         {txt}min = {res}         1
{txt}     between = {res}0.4834                                         {txt}avg = {res}       3.1
{txt}     overall = {res}0.3310                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}37{txt})     =  {res} 11280.26
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:9,851} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0310023{col 30}{space 2} .0097846{col 41}{space 1}    3.17{col 50}{space 3}0.002{col 58}{space 4} .0118249{col 71}{space 3} .0501797
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0017411{col 30}{space 2} .0002489{col 41}{space 1}   -6.99{col 50}{space 3}0.000{col 58}{space 4} -.002229{col 71}{space 3}-.0012533
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0068937{col 30}{space 2} .0040073{col 41}{space 1}   -1.72{col 50}{space 3}0.085{col 58}{space 4}-.0147479{col 71}{space 3} .0009605
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  -.04666{col 30}{space 2} .0407072{col 41}{space 1}   -1.15{col 50}{space 3}0.252{col 58}{space 4}-.1264447{col 71}{space 3} .0331247
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0038973{col 30}{space 2}  .000773{col 41}{space 1}   -5.04{col 50}{space 3}0.000{col 58}{space 4}-.0054124{col 71}{space 3}-.0023822
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0099109{col 30}{space 2} .0251904{col 41}{space 1}   -0.39{col 50}{space 3}0.694{col 58}{space 4}-.0592832{col 71}{space 3} .0394614
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2567841{col 30}{space 2} .0209523{col 41}{space 1}   12.26{col 50}{space 3}0.000{col 58}{space 4} .2157183{col 71}{space 3} .2978498
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1219238{col 30}{space 2}  .043056{col 41}{space 1}    2.83{col 50}{space 3}0.005{col 58}{space 4} .0375355{col 71}{space 3} .2063121
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1827762{col 30}{space 2} .0254795{col 41}{space 1}    7.17{col 50}{space 3}0.000{col 58}{space 4} .1328373{col 71}{space 3} .2327152
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1757753{col 30}{space 2}  .031171{col 41}{space 1}    5.64{col 50}{space 3}0.000{col 58}{space 4} .1146813{col 71}{space 3} .2368692
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1261439{col 30}{space 2} .0287489{col 41}{space 1}    4.39{col 50}{space 3}0.000{col 58}{space 4} .0697971{col 71}{space 3} .1824906
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1543402{col 30}{space 2} .0245491{col 41}{space 1}    6.29{col 50}{space 3}0.000{col 58}{space 4} .1062249{col 71}{space 3} .2024555
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1058237{col 30}{space 2} .0191694{col 41}{space 1}   -5.52{col 50}{space 3}0.000{col 58}{space 4} -.143395{col 71}{space 3}-.0682523
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}  .002002{col 30}{space 2} .0013646{col 41}{space 1}    1.47{col 50}{space 3}0.142{col 58}{space 4}-.0006725{col 71}{space 3} .0046765
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0396084{col 30}{space 2} .0240346{col 41}{space 1}    1.65{col 50}{space 3}0.099{col 58}{space 4}-.0074986{col 71}{space 3} .0867154
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0308281{col 30}{space 2} .0640834{col 41}{space 1}    0.48{col 50}{space 3}0.630{col 58}{space 4} -.094773{col 71}{space 3} .1564292
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5333032{col 30}{space 2} .0407383{col 41}{space 1}   13.09{col 50}{space 3}0.000{col 58}{space 4} .4534575{col 71}{space 3} .6131488
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7145979{col 30}{space 2} .0474424{col 41}{space 1}   15.06{col 50}{space 3}0.000{col 58}{space 4} .6216126{col 71}{space 3} .8075832
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3506405{col 30}{space 2} .0490058{col 41}{space 1}    7.16{col 50}{space 3}0.000{col 58}{space 4} .2545908{col 71}{space 3} .4466901
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2076799{col 30}{space 2} .0376174{col 41}{space 1}    5.52{col 50}{space 3}0.000{col 58}{space 4} .1339512{col 71}{space 3} .2814086
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.6857422{col 30}{space 2} .0644022{col 41}{space 1}  -10.65{col 50}{space 3}0.000{col 58}{space 4}-.8119681{col 71}{space 3}-.5595163
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0847533{col 30}{space 2} .0138479{col 41}{space 1}    6.12{col 50}{space 3}0.000{col 58}{space 4}  .057612{col 71}{space 3} .1118947
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2} .1095648{col 30}{space 2} .0718555{col 41}{space 1}    1.52{col 50}{space 3}0.127{col 58}{space 4}-.0312695{col 71}{space 3}  .250399
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.597128{col 30}{space 2} .0432164{col 41}{space 1}  -36.96{col 50}{space 3}0.000{col 58}{space 4} -1.68183{col 71}{space 3}-1.512425
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.2070273{col 30}{space 2} .0572772{col 41}{space 1}   -3.61{col 50}{space 3}0.000{col 58}{space 4}-.3192886{col 71}{space 3} -.094766
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2} .6543047{col 30}{space 2} .1223747{col 41}{space 1}    5.35{col 50}{space 3}0.000{col 58}{space 4} .4144547{col 71}{space 3} .8941547
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2}  .284467{col 30}{space 2} .0523245{col 41}{space 1}    5.44{col 50}{space 3}0.000{col 58}{space 4} .1819128{col 71}{space 3} .3870212
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.0442746{col 30}{space 2} .1009816{col 41}{space 1}   -0.44{col 50}{space 3}0.661{col 58}{space 4} -.242195{col 71}{space 3} .1536458
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0802643{col 30}{space 2} .0912429{col 41}{space 1}    0.88{col 50}{space 3}0.379{col 58}{space 4}-.0985685{col 71}{space 3} .2590971
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .1257389{col 30}{space 2} .0921265{col 41}{space 1}    1.36{col 50}{space 3}0.172{col 58}{space 4}-.0548258{col 71}{space 3} .3063037
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .2010065{col 30}{space 2} .0949221{col 41}{space 1}    2.12{col 50}{space 3}0.034{col 58}{space 4} .0149626{col 71}{space 3} .3870505
{txt}{space 11}2013  {c |}{col 18}{res}{space 2}  .257885{col 30}{space 2} .0938792{col 41}{space 1}    2.75{col 50}{space 3}0.006{col 58}{space 4} .0738851{col 71}{space 3}  .441885
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.2560868{col 30}{space 2}  .094976{col 41}{space 1}   -2.70{col 50}{space 3}0.007{col 58}{space 4}-.4422364{col 71}{space 3}-.0699372
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .3929515{col 30}{space 2} .0937751{col 41}{space 1}    4.19{col 50}{space 3}0.000{col 58}{space 4} .2091558{col 71}{space 3} .5767473
{txt}{space 11}2016  {c |}{col 18}{res}{space 2} .0986182{col 30}{space 2} .1060803{col 41}{space 1}    0.93{col 50}{space 3}0.353{col 58}{space 4}-.1092953{col 71}{space 3} .3065318
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .6559466{col 30}{space 2} .0963886{col 41}{space 1}    6.81{col 50}{space 3}0.000{col 58}{space 4} .4670285{col 71}{space 3} .8448647
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .3936779{col 30}{space 2} .0969819{col 41}{space 1}    4.06{col 50}{space 3}0.000{col 58}{space 4} .2035969{col 71}{space 3} .5837589
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.564481{col 30}{space 2} .1264425{col 41}{space 1}   36.10{col 50}{space 3}0.000{col 58}{space 4} 4.316658{col 71}{space 3} 4.812304
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .71318524
         {txt}sigma_e {c |} {res} 1.2160383
             {txt}rho {c |} {res} .25593122{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,299
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,149

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0248                                         {txt}min = {res}         1
{txt}     between = {res}0.3154                                         {txt}avg = {res}       3.0
{txt}     overall = {res}0.2003                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1672.00
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,149} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0629351{col 30}{space 2} .0167684{col 41}{space 1}    3.75{col 50}{space 3}0.000{col 58}{space 4} .0300697{col 71}{space 3} .0958006
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0059635{col 30}{space 2} .0006465{col 41}{space 1}   -9.23{col 50}{space 3}0.000{col 58}{space 4}-.0072306{col 71}{space 3}-.0046965
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0565446{col 30}{space 2} .0084454{col 41}{space 1}    6.70{col 50}{space 3}0.000{col 58}{space 4} .0399918{col 71}{space 3} .0730973
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0521073{col 30}{space 2} .0650374{col 41}{space 1}   -0.80{col 50}{space 3}0.423{col 58}{space 4}-.1795783{col 71}{space 3} .0753636
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0019331{col 30}{space 2} .0012056{col 41}{space 1}   -1.60{col 50}{space 3}0.109{col 58}{space 4}-.0042961{col 71}{space 3}   .00043
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0418495{col 30}{space 2} .0409322{col 41}{space 1}   -1.02{col 50}{space 3}0.307{col 58}{space 4}-.1220751{col 71}{space 3} .0383762
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2947527{col 30}{space 2} .0334645{col 41}{space 1}    8.81{col 50}{space 3}0.000{col 58}{space 4} .2291635{col 71}{space 3} .3603419
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2318919{col 30}{space 2} .1594666{col 41}{space 1}   -1.45{col 50}{space 3}0.146{col 58}{space 4}-.5444407{col 71}{space 3} .0806569
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1815826{col 30}{space 2} .0399946{col 41}{space 1}    4.54{col 50}{space 3}0.000{col 58}{space 4} .1031946{col 71}{space 3} .2599706
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1043484{col 30}{space 2} .0499766{col 41}{space 1}    2.09{col 50}{space 3}0.037{col 58}{space 4} .0063961{col 71}{space 3} .2023006
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0615958{col 30}{space 2} .0721464{col 41}{space 1}    0.85{col 50}{space 3}0.393{col 58}{space 4}-.0798086{col 71}{space 3} .2030002
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .195239{col 30}{space 2} .0522673{col 41}{space 1}    3.74{col 50}{space 3}0.000{col 58}{space 4} .0927971{col 71}{space 3}  .297681
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1124402{col 30}{space 2} .0314923{col 41}{space 1}   -3.57{col 50}{space 3}0.000{col 58}{space 4} -.174164{col 71}{space 3}-.0507163
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0141632{col 30}{space 2} .0039231{col 41}{space 1}    3.61{col 50}{space 3}0.000{col 58}{space 4}  .006474{col 71}{space 3} .0218523
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2376595{col 30}{space 2} .0353557{col 41}{space 1}    6.72{col 50}{space 3}0.000{col 58}{space 4} .1683636{col 71}{space 3} .3069553
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .9934979{col 30}{space 2} .2964795{col 41}{space 1}    3.35{col 50}{space 3}0.001{col 58}{space 4} .4124088{col 71}{space 3} 1.574587
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3936754{col 30}{space 2} .0619008{col 41}{space 1}    6.36{col 50}{space 3}0.000{col 58}{space 4} .2723521{col 71}{space 3} .5149987
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4298823{col 30}{space 2}  .075678{col 41}{space 1}    5.68{col 50}{space 3}0.000{col 58}{space 4} .2815561{col 71}{space 3} .5782085
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4923337{col 30}{space 2} .1335268{col 41}{space 1}    3.69{col 50}{space 3}0.000{col 58}{space 4} .2306259{col 71}{space 3} .7540414
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1437998{col 30}{space 2}  .068915{col 41}{space 1}    2.09{col 50}{space 3}0.037{col 58}{space 4} .0087288{col 71}{space 3} .2788707
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .2029988{col 30}{space 2} .1320565{col 41}{space 1}    1.54{col 50}{space 3}0.124{col 58}{space 4}-.0558272{col 71}{space 3} .4618248
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2}  .126247{col 30}{space 2} .0221529{col 41}{space 1}    5.70{col 50}{space 3}0.000{col 58}{space 4} .0828282{col 71}{space 3} .1696659
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.2150037{col 30}{space 2} .0303726{col 41}{space 1}   -7.08{col 50}{space 3}0.000{col 58}{space 4}-.2745328{col 71}{space 3}-.1554745
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.159891{col 30}{space 2}  .158361{col 41}{space 1}   13.64{col 50}{space 3}0.000{col 58}{space 4} 1.849509{col 71}{space 3} 2.470273
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .65885635
         {txt}sigma_e {c |} {res} 1.0648865
             {txt}rho {c |} {res} .27683096{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_MALAWI  if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,301
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,381

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0201                                         {txt}min = {res}         1
{txt}     between = {res}0.4077                                         {txt}avg = {res}       3.1
{txt}     overall = {res}0.2754                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1408.54
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,381} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0393834{col 30}{space 2} .0275167{col 41}{space 1}    1.43{col 50}{space 3}0.152{col 58}{space 4}-.0145484{col 71}{space 3} .0933152
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0138881{col 30}{space 2} .0036226{col 41}{space 1}   -3.83{col 50}{space 3}0.000{col 58}{space 4}-.0209883{col 71}{space 3} -.006788
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0050308{col 30}{space 2} .0123757{col 41}{space 1}   -0.41{col 50}{space 3}0.684{col 58}{space 4}-.0292867{col 71}{space 3} .0192251
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2778643{col 30}{space 2} .1067837{col 41}{space 1}   -2.60{col 50}{space 3}0.009{col 58}{space 4}-.4871566{col 71}{space 3} -.068572
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0025404{col 30}{space 2}   .00199{col 41}{space 1}   -1.28{col 50}{space 3}0.202{col 58}{space 4}-.0064407{col 71}{space 3} .0013599
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0862398{col 30}{space 2} .0626945{col 41}{space 1}   -1.38{col 50}{space 3}0.169{col 58}{space 4}-.2091188{col 71}{space 3} .0366391
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3093096{col 30}{space 2} .0604271{col 41}{space 1}    5.12{col 50}{space 3}0.000{col 58}{space 4} .1908746{col 71}{space 3} .4277445
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2138721{col 30}{space 2} .1970947{col 41}{space 1}    1.09{col 50}{space 3}0.278{col 58}{space 4}-.1724265{col 71}{space 3} .6001707
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0895435{col 30}{space 2}  .071579{col 41}{space 1}    1.25{col 50}{space 3}0.211{col 58}{space 4}-.0507488{col 71}{space 3} .2298358
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1792655{col 30}{space 2} .1450434{col 41}{space 1}    1.24{col 50}{space 3}0.216{col 58}{space 4}-.1050143{col 71}{space 3} .4635453
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .139177{col 30}{space 2} .0832823{col 41}{space 1}    1.67{col 50}{space 3}0.095{col 58}{space 4}-.0240534{col 71}{space 3} .3024074
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2251155{col 30}{space 2} .0576772{col 41}{space 1}    3.90{col 50}{space 3}0.000{col 58}{space 4} .1120702{col 71}{space 3} .3381607
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1898957{col 30}{space 2} .0467547{col 41}{space 1}   -4.06{col 50}{space 3}0.000{col 58}{space 4}-.2815332{col 71}{space 3}-.0982582
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0857283{col 30}{space 2} .0382634{col 41}{space 1}    2.24{col 50}{space 3}0.025{col 58}{space 4} .0107334{col 71}{space 3} .1607231
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0467283{col 30}{space 2} .0655529{col 41}{space 1}    0.71{col 50}{space 3}0.476{col 58}{space 4}-.0817531{col 71}{space 3} .1752097
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0426761{col 30}{space 2} .3327432{col 41}{space 1}    0.13{col 50}{space 3}0.898{col 58}{space 4}-.6094886{col 71}{space 3} .6948409
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7393148{col 30}{space 2} .1134615{col 41}{space 1}    6.52{col 50}{space 3}0.000{col 58}{space 4} .5169344{col 71}{space 3} .9616952
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8826359{col 30}{space 2} .1845785{col 41}{space 1}    4.78{col 50}{space 3}0.000{col 58}{space 4} .5208686{col 71}{space 3} 1.244403
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3987252{col 30}{space 2} .1191877{col 41}{space 1}    3.35{col 50}{space 3}0.001{col 58}{space 4} .1651215{col 71}{space 3} .6323289
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2999147{col 30}{space 2} .1050693{col 41}{space 1}    2.85{col 50}{space 3}0.004{col 58}{space 4} .0939827{col 71}{space 3} .5058467
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.3984307{col 30}{space 2} .2007614{col 41}{space 1}   -1.98{col 50}{space 3}0.047{col 58}{space 4}-.7919159{col 71}{space 3}-.0049455
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2}-.0412983{col 30}{space 2} .0410157{col 41}{space 1}   -1.01{col 50}{space 3}0.314{col 58}{space 4}-.1216876{col 71}{space 3} .0390911
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .0457969{col 30}{space 2} .1207345{col 41}{space 1}    0.38{col 50}{space 3}0.704{col 58}{space 4}-.1908383{col 71}{space 3} .2824322
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.0151845{col 30}{space 2} .0859077{col 41}{space 1}   -0.18{col 50}{space 3}0.860{col 58}{space 4}-.1835606{col 71}{space 3} .1531916
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.657393{col 30}{space 2} .3345308{col 41}{space 1}   16.91{col 50}{space 3}0.000{col 58}{space 4} 5.001725{col 71}{space 3} 6.313061
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .68194604
         {txt}sigma_e {c |} {res} 1.2921011
             {txt}rho {c |} {res} .21786551{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9 pdd9_town sum_town  $xlist  pdd9_mean_town $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,552
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,853

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0348                                         {txt}min = {res}         1
{txt}     between = {res}0.2641                                         {txt}avg = {res}       1.9
{txt}     overall = {res}0.1797                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1177.52
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,853} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0733169{col 30}{space 2} .0299422{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4} .0146312{col 71}{space 3} .1320026
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2} -.001297{col 30}{space 2} .0003733{col 41}{space 1}   -3.47{col 50}{space 3}0.001{col 58}{space 4}-.0020287{col 71}{space 3}-.0005653
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0087827{col 30}{space 2} .0086123{col 41}{space 1}   -1.02{col 50}{space 3}0.308{col 58}{space 4}-.0256625{col 71}{space 3} .0080972
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1203634{col 30}{space 2} .1107974{col 41}{space 1}   -1.09{col 50}{space 3}0.277{col 58}{space 4}-.3375224{col 71}{space 3} .0967955
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0006799{col 30}{space 2} .0018917{col 41}{space 1}   -0.36{col 50}{space 3}0.719{col 58}{space 4}-.0043875{col 71}{space 3} .0030277
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1029425{col 30}{space 2} .0638596{col 41}{space 1}    1.61{col 50}{space 3}0.107{col 58}{space 4}  -.02222{col 71}{space 3} .2281049
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .289967{col 30}{space 2} .0500698{col 41}{space 1}    5.79{col 50}{space 3}0.000{col 58}{space 4} .1918319{col 71}{space 3} .3881021
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3187904{col 30}{space 2} .1109293{col 41}{space 1}    2.87{col 50}{space 3}0.004{col 58}{space 4}  .101373{col 71}{space 3} .5362079
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1570413{col 30}{space 2} .0790462{col 41}{space 1}    1.99{col 50}{space 3}0.047{col 58}{space 4} .0021135{col 71}{space 3}  .311969
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3150548{col 30}{space 2} .1259174{col 41}{space 1}    2.50{col 50}{space 3}0.012{col 58}{space 4} .0682613{col 71}{space 3} .5618484
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2013966{col 30}{space 2} .0902726{col 41}{space 1}    2.23{col 50}{space 3}0.026{col 58}{space 4} .0244656{col 71}{space 3} .3783276
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1869683{col 30}{space 2} .0699475{col 41}{space 1}   -2.67{col 50}{space 3}0.008{col 58}{space 4} -.324063{col 71}{space 3}-.0498737
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1640332{col 30}{space 2} .0486808{col 41}{space 1}   -3.37{col 50}{space 3}0.001{col 58}{space 4}-.2594458{col 71}{space 3}-.0686206
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0003427{col 30}{space 2} .0018215{col 41}{space 1}    0.19{col 50}{space 3}0.851{col 58}{space 4}-.0032274{col 71}{space 3} .0039128
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0581401{col 30}{space 2} .2394193{col 41}{space 1}    0.24{col 50}{space 3}0.808{col 58}{space 4}-.4111131{col 71}{space 3} .5273934
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0676676{col 30}{space 2}  .139774{col 41}{space 1}    0.48{col 50}{space 3}0.628{col 58}{space 4}-.2062843{col 71}{space 3} .3416195
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .363886{col 30}{space 2} .1020969{col 41}{space 1}    3.56{col 50}{space 3}0.000{col 58}{space 4} .1637798{col 71}{space 3} .5639923
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5686258{col 30}{space 2} .1459845{col 41}{space 1}    3.90{col 50}{space 3}0.000{col 58}{space 4} .2825014{col 71}{space 3} .8547502
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2346352{col 30}{space 2} .1180364{col 41}{space 1}    1.99{col 50}{space 3}0.047{col 58}{space 4} .0032882{col 71}{space 3} .4659823
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4695394{col 30}{space 2}   .08968{col 41}{space 1}    5.24{col 50}{space 3}0.000{col 58}{space 4} .2937699{col 71}{space 3} .6453089
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-1.168121{col 30}{space 2} .3334021{col 41}{space 1}   -3.50{col 50}{space 3}0.000{col 58}{space 4}-1.821578{col 71}{space 3}-.5146652
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0603068{col 30}{space 2} .0384583{col 41}{space 1}    1.57{col 50}{space 3}0.117{col 58}{space 4}  -.01507{col 71}{space 3} .1356837
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}  .588589{col 30}{space 2}    .0995{col 41}{space 1}    5.92{col 50}{space 3}0.000{col 58}{space 4} .3935725{col 71}{space 3} .7836055
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.221349{col 30}{space 2} .2050494{col 41}{space 1}   20.59{col 50}{space 3}0.000{col 58}{space 4} 3.819459{col 71}{space 3} 4.623238
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .55121233
         {txt}sigma_e {c |} {res} 1.3919263
             {txt}rho {c |} {res} .13556233{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,014
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,108

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0662                                         {txt}min = {res}         1
{txt}     between = {res}0.4101                                         {txt}avg = {res}       3.6
{txt}     overall = {res}0.2545                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}25{txt})     =  {res}   943.46
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,108} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2}  .088998{col 30}{space 2} .0251729{col 41}{space 1}    3.54{col 50}{space 3}0.000{col 58}{space 4} .0396599{col 71}{space 3} .1383361
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2} -.024926{col 30}{space 2} .0051475{col 41}{space 1}   -4.84{col 50}{space 3}0.000{col 58}{space 4} -.035015{col 71}{space 3} -.014837
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0003602{col 30}{space 2} .0109893{col 41}{space 1}   -0.03{col 50}{space 3}0.974{col 58}{space 4}-.0218988{col 71}{space 3} .0211784
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0009234{col 30}{space 2} .1056918{col 41}{space 1}   -0.01{col 50}{space 3}0.993{col 58}{space 4}-.2080755{col 71}{space 3} .2062287
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0049736{col 30}{space 2} .0026688{col 41}{space 1}    1.86{col 50}{space 3}0.062{col 58}{space 4}-.0002571{col 71}{space 3} .0102042
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1301475{col 30}{space 2}   .07551{col 41}{space 1}    1.72{col 50}{space 3}0.085{col 58}{space 4}-.0178493{col 71}{space 3} .2781443
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0558474{col 30}{space 2} .0511666{col 41}{space 1}    1.09{col 50}{space 3}0.275{col 58}{space 4}-.0444373{col 71}{space 3} .1561322
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0453488{col 30}{space 2} .0700769{col 41}{space 1}    0.65{col 50}{space 3}0.518{col 58}{space 4}-.0919994{col 71}{space 3}  .182697
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1867039{col 30}{space 2} .0688571{col 41}{space 1}    2.71{col 50}{space 3}0.007{col 58}{space 4} .0517464{col 71}{space 3} .3216614
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1104693{col 30}{space 2} .0904186{col 41}{space 1}    1.22{col 50}{space 3}0.222{col 58}{space 4} -.066748{col 71}{space 3} .2876866
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .266623{col 30}{space 2}  .095115{col 41}{space 1}    2.80{col 50}{space 3}0.005{col 58}{space 4} .0802011{col 71}{space 3} .4530449
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3061706{col 30}{space 2} .0675783{col 41}{space 1}    4.53{col 50}{space 3}0.000{col 58}{space 4} .1737195{col 71}{space 3} .4386216
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0322942{col 30}{space 2} .0901716{col 41}{space 1}    0.36{col 50}{space 3}0.720{col 58}{space 4} -.144439{col 71}{space 3} .2090273
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0019465{col 30}{space 2} .0129527{col 41}{space 1}    0.15{col 50}{space 3}0.881{col 58}{space 4}-.0234403{col 71}{space 3} .0273334
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1686468{col 30}{space 2} .1257962{col 41}{space 1}    1.34{col 50}{space 3}0.180{col 58}{space 4}-.0779092{col 71}{space 3} .4152027
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0563308{col 30}{space 2} .1120748{col 41}{space 1}   -0.50{col 50}{space 3}0.615{col 58}{space 4}-.2759933{col 71}{space 3} .1633317
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .9257016{col 30}{space 2} .1284671{col 41}{space 1}    7.21{col 50}{space 3}0.000{col 58}{space 4} .6739108{col 71}{space 3} 1.177492
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8161456{col 30}{space 2} .1200833{col 41}{space 1}    6.80{col 50}{space 3}0.000{col 58}{space 4} .5807868{col 71}{space 3} 1.051505
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0864811{col 30}{space 2} .1434428{col 41}{space 1}    0.60{col 50}{space 3}0.547{col 58}{space 4}-.1946615{col 71}{space 3} .3676238
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0883284{col 30}{space 2} .1041764{col 41}{space 1}   -0.85{col 50}{space 3}0.397{col 58}{space 4}-.2925104{col 71}{space 3} .1158535
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .0100867{col 30}{space 2} .2186781{col 41}{space 1}    0.05{col 50}{space 3}0.963{col 58}{space 4}-.4185144{col 71}{space 3} .4386879
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0800589{col 30}{space 2}  .038638{col 41}{space 1}    2.07{col 50}{space 3}0.038{col 58}{space 4} .0043298{col 71}{space 3}  .155788
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.6231571{col 30}{space 2} .0648686{col 41}{space 1}   -9.61{col 50}{space 3}0.000{col 58}{space 4}-.7502972{col 71}{space 3} -.496017
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.5234528{col 30}{space 2}   .06144{col 41}{space 1}   -8.52{col 50}{space 3}0.000{col 58}{space 4} -.643873{col 71}{space 3}-.4030326
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.4113021{col 30}{space 2} .0592166{col 41}{space 1}   -6.95{col 50}{space 3}0.000{col 58}{space 4}-.5273645{col 71}{space 3}-.2952396
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.983209{col 30}{space 2} .4580877{col 41}{space 1}    8.70{col 50}{space 3}0.000{col 58}{space 4} 3.085374{col 71}{space 3} 4.881045
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .67801906
         {txt}sigma_e {c |} {res} 1.2395582
             {txt}rho {c |} {res} .23029082{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     1,113
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}       271

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0628                                         {txt}min = {res}         1
{txt}     between = {res}0.4080                                         {txt}avg = {res}       4.1
{txt}     overall = {res}0.2763                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}25{txt})     =  {res}   323.39
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:271} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0025379{col 30}{space 2} .0467482{col 41}{space 1}    0.05{col 50}{space 3}0.957{col 58}{space 4}-.0890868{col 71}{space 3} .0941626
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2} -.008913{col 30}{space 2} .0139239{col 41}{space 1}   -0.64{col 50}{space 3}0.522{col 58}{space 4}-.0362034{col 71}{space 3} .0183774
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.1088701{col 30}{space 2} .0218825{col 41}{space 1}   -4.98{col 50}{space 3}0.000{col 58}{space 4} -.151759{col 71}{space 3}-.0659813
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .3522011{col 30}{space 2} .2147236{col 41}{space 1}    1.64{col 50}{space 3}0.101{col 58}{space 4}-.0686494{col 71}{space 3} .7730516
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.021819{col 30}{space 2}  .004547{col 41}{space 1}   -4.80{col 50}{space 3}0.000{col 58}{space 4}-.0307309{col 71}{space 3} -.012907
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3561101{col 30}{space 2}  .126706{col 41}{space 1}    2.81{col 50}{space 3}0.005{col 58}{space 4} .1077709{col 71}{space 3} .6044493
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1158421{col 30}{space 2} .1241158{col 41}{space 1}    0.93{col 50}{space 3}0.351{col 58}{space 4}-.1274204{col 71}{space 3} .3591046
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1975007{col 30}{space 2} .1782427{col 41}{space 1}    1.11{col 50}{space 3}0.268{col 58}{space 4}-.1518486{col 71}{space 3}   .54685
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3346579{col 30}{space 2} .1202644{col 41}{space 1}    2.78{col 50}{space 3}0.005{col 58}{space 4}  .098944{col 71}{space 3} .5703718
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1958896{col 30}{space 2}  .130601{col 41}{space 1}    1.50{col 50}{space 3}0.134{col 58}{space 4}-.0600836{col 71}{space 3} .4518628
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0973472{col 30}{space 2} .0935652{col 41}{space 1}    1.04{col 50}{space 3}0.298{col 58}{space 4}-.0860373{col 71}{space 3} .2807317
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1882103{col 30}{space 2} .1046232{col 41}{space 1}    1.80{col 50}{space 3}0.072{col 58}{space 4}-.0168473{col 71}{space 3}  .393268
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.230411{col 30}{space 2} .1096737{col 41}{space 1}   -2.10{col 50}{space 3}0.036{col 58}{space 4}-.4453676{col 71}{space 3}-.0154544
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0091601{col 30}{space 2} .0136674{col 41}{space 1}    0.67{col 50}{space 3}0.503{col 58}{space 4}-.0176276{col 71}{space 3} .0359477
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.2670728{col 30}{space 2} .1135907{col 41}{space 1}   -2.35{col 50}{space 3}0.019{col 58}{space 4}-.4897065{col 71}{space 3} -.044439
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .7928131{col 30}{space 2} .3503349{col 41}{space 1}    2.26{col 50}{space 3}0.024{col 58}{space 4} .1061693{col 71}{space 3} 1.479457
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7529794{col 30}{space 2} .2350841{col 41}{space 1}    3.20{col 50}{space 3}0.001{col 58}{space 4}  .292223{col 71}{space 3} 1.213736
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.063463{col 30}{space 2} .2497835{col 41}{space 1}    4.26{col 50}{space 3}0.000{col 58}{space 4} .5738965{col 71}{space 3}  1.55303
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} -.123941{col 30}{space 2} .2110437{col 41}{space 1}   -0.59{col 50}{space 3}0.557{col 58}{space 4} -.537579{col 71}{space 3} .2896969
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1559515{col 30}{space 2}  .219574{col 41}{space 1}    0.71{col 50}{space 3}0.478{col 58}{space 4}-.2744056{col 71}{space 3} .5863085
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-1.805901{col 30}{space 2} .2576799{col 41}{space 1}   -7.01{col 50}{space 3}0.000{col 58}{space 4}-2.310945{col 71}{space 3}-1.300858
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2}-.1549613{col 30}{space 2} .0844113{col 41}{space 1}   -1.84{col 50}{space 3}0.066{col 58}{space 4}-.3204044{col 71}{space 3} .0104819
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.2921562{col 30}{space 2} .1166391{col 41}{space 1}   -2.50{col 50}{space 3}0.012{col 58}{space 4}-.5207647{col 71}{space 3}-.0635477
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0492952{col 30}{space 2}  .092084{col 41}{space 1}    0.54{col 50}{space 3}0.592{col 58}{space 4} -.131186{col 71}{space 3} .2297765
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.0423268{col 30}{space 2}  .100676{col 41}{space 1}   -0.42{col 50}{space 3}0.674{col 58}{space 4}-.2396481{col 71}{space 3} .1549944
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 10.33404{col 30}{space 2} .9295309{col 41}{space 1}   11.12{col 50}{space 3}0.000{col 58}{space 4} 8.512195{col 71}{space 3} 12.15589
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .74979659
         {txt}sigma_e {c |} {res} 1.1395259
             {txt}rho {c |} {res} .30213933{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     6,588
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,089

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0748                                         {txt}min = {res}         1
{txt}     between = {res}0.3106                                         {txt}avg = {res}       6.0
{txt}     overall = {res}0.1910                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}27{txt})     =  {res}   983.38
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,089} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0107323{col 30}{space 2} .0204502{col 41}{space 1}    0.52{col 50}{space 3}0.600{col 58}{space 4}-.0293493{col 71}{space 3} .0508138
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0162783{col 30}{space 2} .0045281{col 41}{space 1}   -3.59{col 50}{space 3}0.000{col 58}{space 4}-.0251533{col 71}{space 3}-.0074033
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0354911{col 30}{space 2} .0097344{col 41}{space 1}   -3.65{col 50}{space 3}0.000{col 58}{space 4}-.0545701{col 71}{space 3}-.0164121
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1010747{col 30}{space 2} .0913738{col 41}{space 1}    1.11{col 50}{space 3}0.269{col 58}{space 4}-.0780146{col 71}{space 3} .2801641
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0084179{col 30}{space 2} .0021511{col 41}{space 1}   -3.91{col 50}{space 3}0.000{col 58}{space 4} -.012634{col 71}{space 3}-.0042019
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0114225{col 30}{space 2} .0557913{col 41}{space 1}    0.20{col 50}{space 3}0.838{col 58}{space 4}-.0979264{col 71}{space 3} .1207715
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2507858{col 30}{space 2} .0516498{col 41}{space 1}    4.86{col 50}{space 3}0.000{col 58}{space 4}  .149554{col 71}{space 3} .3520176
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1525732{col 30}{space 2} .0754281{col 41}{space 1}    2.02{col 50}{space 3}0.043{col 58}{space 4} .0047369{col 71}{space 3} .3004095
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3493906{col 30}{space 2} .0518845{col 41}{space 1}    6.73{col 50}{space 3}0.000{col 58}{space 4} .2476989{col 71}{space 3} .4510823
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4583741{col 30}{space 2}  .053826{col 41}{space 1}    8.52{col 50}{space 3}0.000{col 58}{space 4} .3528772{col 71}{space 3} .5638711
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0528196{col 30}{space 2} .0419519{col 41}{space 1}    1.26{col 50}{space 3}0.208{col 58}{space 4}-.0294046{col 71}{space 3} .1350437
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1444329{col 30}{space 2} .0447911{col 41}{space 1}    3.22{col 50}{space 3}0.001{col 58}{space 4} .0566441{col 71}{space 3} .2322218
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0299922{col 30}{space 2} .0364598{col 41}{space 1}   -0.82{col 50}{space 3}0.411{col 58}{space 4}-.1014521{col 71}{space 3} .0414676
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0059377{col 30}{space 2} .0016882{col 41}{space 1}    3.52{col 50}{space 3}0.000{col 58}{space 4}  .002629{col 71}{space 3} .0092464
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.2159297{col 30}{space 2} .0469381{col 41}{space 1}   -4.60{col 50}{space 3}0.000{col 58}{space 4}-.3079266{col 71}{space 3}-.1239328
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1239437{col 30}{space 2} .1420037{col 41}{space 1}    0.87{col 50}{space 3}0.383{col 58}{space 4}-.1543784{col 71}{space 3} .4022659
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .2450766{col 30}{space 2} .1073774{col 41}{space 1}    2.28{col 50}{space 3}0.022{col 58}{space 4} .0346207{col 71}{space 3} .4555324
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5428035{col 30}{space 2} .1366015{col 41}{space 1}    3.97{col 50}{space 3}0.000{col 58}{space 4} .2750696{col 71}{space 3} .8105375
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1614056{col 30}{space 2}  .099893{col 41}{space 1}    1.62{col 50}{space 3}0.106{col 58}{space 4} -.034381{col 71}{space 3} .3571923
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3471735{col 30}{space 2} .0913323{col 41}{space 1}    3.80{col 50}{space 3}0.000{col 58}{space 4} .1681655{col 71}{space 3} .5261816
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-1.225566{col 30}{space 2} .1608307{col 41}{space 1}   -7.62{col 50}{space 3}0.000{col 58}{space 4}-1.540789{col 71}{space 3} -.910344
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .1307386{col 30}{space 2} .0393155{col 41}{space 1}    3.33{col 50}{space 3}0.001{col 58}{space 4} .0536816{col 71}{space 3} .2077956
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.2665617{col 30}{space 2} .0600059{col 41}{space 1}   -4.44{col 50}{space 3}0.000{col 58}{space 4}-.3841712{col 71}{space 3}-.1489523
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.1300695{col 30}{space 2} .0500477{col 41}{space 1}   -2.60{col 50}{space 3}0.009{col 58}{space 4}-.2281611{col 71}{space 3}-.0319778
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .4023845{col 30}{space 2} .0498505{col 41}{space 1}    8.07{col 50}{space 3}0.000{col 58}{space 4} .3046793{col 71}{space 3} .5000897
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .2253497{col 30}{space 2} .0508512{col 41}{space 1}    4.43{col 50}{space 3}0.000{col 58}{space 4} .1256832{col 71}{space 3} .3250161
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .4026888{col 30}{space 2} .0488202{col 41}{space 1}    8.25{col 50}{space 3}0.000{col 58}{space 4}  .307003{col 71}{space 3} .4983745
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.472804{col 30}{space 2} .3664464{col 41}{space 1}   14.93{col 50}{space 3}0.000{col 58}{space 4} 4.754582{col 71}{space 3} 6.191025
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69562466
         {txt}sigma_e {c |} {res} 1.2199703
             {txt}rho {c |} {res} .24535465{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S17_balance_imr.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9_town    $xlist  pdd9_mean_town sum_town _cons)
{res}{txt}(note: file S17_balance_imr.rtf not found)
(output written to {browse  `"S17_balance_imr.rtf"'})

{com}. 
. 
. 
. 
. *                          dist_village_level                                  *
. 
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist i.country i.year   , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    30,867
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     9,851

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0394                                         {txt}min = {res}         1
{txt}     between = {res}0.4835                                         {txt}avg = {res}       3.1
{txt}     overall = {res}0.3310                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}37{txt})     =  {res} 11399.22
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:9,851} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0440938{col 30}{space 2} .0114647{col 41}{space 1}    3.85{col 50}{space 3}0.000{col 58}{space 4} .0216234{col 71}{space 3} .0665643
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2} -.001319{col 30}{space 2}  .000215{col 41}{space 1}   -6.14{col 50}{space 3}0.000{col 58}{space 4}-.0017404{col 71}{space 3}-.0008977
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0076453{col 30}{space 2} .0040139{col 41}{space 1}   -1.90{col 50}{space 3}0.057{col 58}{space 4}-.0155124{col 71}{space 3} .0002218
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0417597{col 30}{space 2} .0406652{col 41}{space 1}   -1.03{col 50}{space 3}0.304{col 58}{space 4}-.1214621{col 71}{space 3} .0379427
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0041398{col 30}{space 2} .0007722{col 41}{space 1}   -5.36{col 50}{space 3}0.000{col 58}{space 4}-.0056532{col 71}{space 3}-.0026263
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0091182{col 30}{space 2} .0251073{col 41}{space 1}   -0.36{col 50}{space 3}0.716{col 58}{space 4}-.0583276{col 71}{space 3} .0400911
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2539517{col 30}{space 2} .0209495{col 41}{space 1}   12.12{col 50}{space 3}0.000{col 58}{space 4} .2128914{col 71}{space 3} .2950119
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1187668{col 30}{space 2}  .042917{col 41}{space 1}    2.77{col 50}{space 3}0.006{col 58}{space 4}  .034651{col 71}{space 3} .2028826
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1852871{col 30}{space 2} .0254382{col 41}{space 1}    7.28{col 50}{space 3}0.000{col 58}{space 4} .1354291{col 71}{space 3}  .235145
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1787804{col 30}{space 2} .0311393{col 41}{space 1}    5.74{col 50}{space 3}0.000{col 58}{space 4} .1177485{col 71}{space 3} .2398123
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}    .1275{col 30}{space 2} .0287466{col 41}{space 1}    4.44{col 50}{space 3}0.000{col 58}{space 4} .0711577{col 71}{space 3} .1838423
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1513931{col 30}{space 2} .0245332{col 41}{space 1}    6.17{col 50}{space 3}0.000{col 58}{space 4} .1033089{col 71}{space 3} .1994773
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1035646{col 30}{space 2} .0192033{col 41}{space 1}   -5.39{col 50}{space 3}0.000{col 58}{space 4}-.1412024{col 71}{space 3}-.0659267
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0022808{col 30}{space 2} .0013731{col 41}{space 1}    1.66{col 50}{space 3}0.097{col 58}{space 4}-.0004104{col 71}{space 3}  .004972
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0255306{col 30}{space 2} .0241896{col 41}{space 1}    1.06{col 50}{space 3}0.291{col 58}{space 4}-.0218802{col 71}{space 3} .0729413
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0536033{col 30}{space 2} .0643667{col 41}{space 1}    0.83{col 50}{space 3}0.405{col 58}{space 4} -.072553{col 71}{space 3} .1797597
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5294821{col 30}{space 2} .0406185{col 41}{space 1}   13.04{col 50}{space 3}0.000{col 58}{space 4} .4498713{col 71}{space 3} .6090929
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6930534{col 30}{space 2} .0474025{col 41}{space 1}   14.62{col 50}{space 3}0.000{col 58}{space 4} .6001462{col 71}{space 3} .7859607
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3426037{col 30}{space 2} .0489622{col 41}{space 1}    7.00{col 50}{space 3}0.000{col 58}{space 4} .2466396{col 71}{space 3} .4385679
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1922766{col 30}{space 2} .0377075{col 41}{space 1}    5.10{col 50}{space 3}0.000{col 58}{space 4} .1183712{col 71}{space 3} .2661821
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.7471387{col 30}{space 2} .0638237{col 41}{space 1}  -11.71{col 50}{space 3}0.000{col 58}{space 4}-.8722307{col 71}{space 3}-.6220466
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0940258{col 30}{space 2} .0160308{col 41}{space 1}    5.87{col 50}{space 3}0.000{col 58}{space 4}  .062606{col 71}{space 3} .1254457
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}   .03124{col 30}{space 2} .0724153{col 41}{space 1}    0.43{col 50}{space 3}0.666{col 58}{space 4}-.1106915{col 71}{space 3} .1731714
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.562099{col 30}{space 2} .0472687{col 41}{space 1}  -33.05{col 50}{space 3}0.000{col 58}{space 4}-1.654744{col 71}{space 3}-1.469454
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.2281181{col 30}{space 2}  .060245{col 41}{space 1}   -3.79{col 50}{space 3}0.000{col 58}{space 4} -.346196{col 71}{space 3}-.1100401
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2} .6967419{col 30}{space 2} .1229642{col 41}{space 1}    5.67{col 50}{space 3}0.000{col 58}{space 4} .4557365{col 71}{space 3} .9377473
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .2659732{col 30}{space 2} .0543359{col 41}{space 1}    4.89{col 50}{space 3}0.000{col 58}{space 4} .1594768{col 71}{space 3} .3724697
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2} -.039728{col 30}{space 2} .1007269{col 41}{space 1}   -0.39{col 50}{space 3}0.693{col 58}{space 4}-.2371492{col 71}{space 3} .1576931
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}  .086459{col 30}{space 2} .0910316{col 41}{space 1}    0.95{col 50}{space 3}0.342{col 58}{space 4}-.0919596{col 71}{space 3} .2648776
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .1392613{col 30}{space 2} .0918748{col 41}{space 1}    1.52{col 50}{space 3}0.130{col 58}{space 4}-.0408099{col 71}{space 3} .3193326
{txt}{space 11}2012  {c |}{col 18}{res}{space 2}  .218095{col 30}{space 2} .0946444{col 41}{space 1}    2.30{col 50}{space 3}0.021{col 58}{space 4} .0325953{col 71}{space 3} .4035946
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .2766566{col 30}{space 2} .0936225{col 41}{space 1}    2.96{col 50}{space 3}0.003{col 58}{space 4} .0931599{col 71}{space 3} .4601534
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.2703809{col 30}{space 2} .0947162{col 41}{space 1}   -2.85{col 50}{space 3}0.004{col 58}{space 4}-.4560212{col 71}{space 3}-.0847406
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .4100811{col 30}{space 2} .0934997{col 41}{space 1}    4.39{col 50}{space 3}0.000{col 58}{space 4} .2268251{col 71}{space 3} .5933371
{txt}{space 11}2016  {c |}{col 18}{res}{space 2} .1203121{col 30}{space 2} .1058508{col 41}{space 1}    1.14{col 50}{space 3}0.256{col 58}{space 4}-.0871515{col 71}{space 3} .3277758
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .6715058{col 30}{space 2} .0963363{col 41}{space 1}    6.97{col 50}{space 3}0.000{col 58}{space 4}   .48269{col 71}{space 3} .8603215
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .4206525{col 30}{space 2} .0967108{col 41}{space 1}    4.35{col 50}{space 3}0.000{col 58}{space 4} .2311029{col 71}{space 3} .6102021
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.400169{col 30}{space 2}   .13451{col 41}{space 1}   32.71{col 50}{space 3}0.000{col 58}{space 4} 4.136534{col 71}{space 3} 4.663803
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .71500038
         {txt}sigma_e {c |} {res} 1.2163198
             {txt}rho {c |} {res} .25681216{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,299
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,149

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0248                                         {txt}min = {res}         1
{txt}     between = {res}0.3149                                         {txt}avg = {res}       3.0
{txt}     overall = {res}0.1995                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1677.07
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,149} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0704786{col 30}{space 2} .0170884{col 41}{space 1}    4.12{col 50}{space 3}0.000{col 58}{space 4}  .036986{col 71}{space 3} .1039712
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0056331{col 30}{space 2} .0006492{col 41}{space 1}   -8.68{col 50}{space 3}0.000{col 58}{space 4}-.0069056{col 71}{space 3}-.0043607
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0563186{col 30}{space 2} .0084448{col 41}{space 1}    6.67{col 50}{space 3}0.000{col 58}{space 4}  .039767{col 71}{space 3} .0728702
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0446468{col 30}{space 2} .0650171{col 41}{space 1}   -0.69{col 50}{space 3}0.492{col 58}{space 4}-.1720779{col 71}{space 3} .0827843
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0022455{col 30}{space 2} .0012053{col 41}{space 1}   -1.86{col 50}{space 3}0.062{col 58}{space 4}-.0046078{col 71}{space 3} .0001169
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0427357{col 30}{space 2} .0408486{col 41}{space 1}   -1.05{col 50}{space 3}0.295{col 58}{space 4}-.1227974{col 71}{space 3} .0373261
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2946974{col 30}{space 2} .0334626{col 41}{space 1}    8.81{col 50}{space 3}0.000{col 58}{space 4}  .229112{col 71}{space 3} .3602828
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2360853{col 30}{space 2} .1598784{col 41}{space 1}   -1.48{col 50}{space 3}0.140{col 58}{space 4}-.5494412{col 71}{space 3} .0772706
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1837089{col 30}{space 2} .0399495{col 41}{space 1}    4.60{col 50}{space 3}0.000{col 58}{space 4} .1054094{col 71}{space 3} .2620084
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1075501{col 30}{space 2} .0499846{col 41}{space 1}    2.15{col 50}{space 3}0.031{col 58}{space 4} .0095821{col 71}{space 3} .2055181
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0606271{col 30}{space 2} .0721406{col 41}{space 1}    0.84{col 50}{space 3}0.401{col 58}{space 4}-.0807659{col 71}{space 3} .2020201
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1938619{col 30}{space 2} .0522589{col 41}{space 1}    3.71{col 50}{space 3}0.000{col 58}{space 4} .0914364{col 71}{space 3} .2962874
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1125594{col 30}{space 2} .0315135{col 41}{space 1}   -3.57{col 50}{space 3}0.000{col 58}{space 4}-.1743248{col 71}{space 3}-.0507941
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0147672{col 30}{space 2} .0039742{col 41}{space 1}    3.72{col 50}{space 3}0.000{col 58}{space 4} .0069779{col 71}{space 3} .0225566
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2391599{col 30}{space 2} .0353123{col 41}{space 1}    6.77{col 50}{space 3}0.000{col 58}{space 4} .1699491{col 71}{space 3} .3083707
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} 1.007935{col 30}{space 2} .2974592{col 41}{space 1}    3.39{col 50}{space 3}0.001{col 58}{space 4} .4249254{col 71}{space 3} 1.590944
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3896676{col 30}{space 2} .0619393{col 41}{space 1}    6.29{col 50}{space 3}0.000{col 58}{space 4} .2682687{col 71}{space 3} .5110664
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .390588{col 30}{space 2} .0757747{col 41}{space 1}    5.15{col 50}{space 3}0.000{col 58}{space 4} .2420722{col 71}{space 3} .5391037
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .5051082{col 30}{space 2} .1331851{col 41}{space 1}    3.79{col 50}{space 3}0.000{col 58}{space 4} .2440702{col 71}{space 3} .7661462
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1306468{col 30}{space 2} .0690592{col 41}{space 1}    1.89{col 50}{space 3}0.059{col 58}{space 4}-.0047068{col 71}{space 3} .2660004
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .1728599{col 30}{space 2} .1313807{col 41}{space 1}    1.32{col 50}{space 3}0.188{col 58}{space 4}-.0846416{col 71}{space 3} .4303614
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2}  .119236{col 30}{space 2} .0225584{col 41}{space 1}    5.29{col 50}{space 3}0.000{col 58}{space 4} .0750224{col 71}{space 3} .1634496
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.2124548{col 30}{space 2} .0303356{col 41}{space 1}   -7.00{col 50}{space 3}0.000{col 58}{space 4}-.2719114{col 71}{space 3}-.1529982
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.176484{col 30}{space 2} .1587157{col 41}{space 1}   13.71{col 50}{space 3}0.000{col 58}{space 4} 1.865407{col 71}{space 3} 2.487561
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .66001391
         {txt}sigma_e {c |} {res} 1.0647155
             {txt}rho {c |} {res} .27759876{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_MALAWI  if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,301
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,381

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0204                                         {txt}min = {res}         1
{txt}     between = {res}0.4125                                         {txt}avg = {res}       3.1
{txt}     overall = {res}0.2765                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1396.71
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,381} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2}-.0380447{col 30}{space 2} .0423324{col 41}{space 1}   -0.90{col 50}{space 3}0.369{col 58}{space 4}-.1210147{col 71}{space 3} .0449253
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0043193{col 30}{space 2} .0010345{col 41}{space 1}   -4.18{col 50}{space 3}0.000{col 58}{space 4}-.0063469{col 71}{space 3}-.0022918
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0048417{col 30}{space 2} .0124187{col 41}{space 1}   -0.39{col 50}{space 3}0.697{col 58}{space 4} -.029182{col 71}{space 3} .0194985
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2938527{col 30}{space 2} .1064494{col 41}{space 1}   -2.76{col 50}{space 3}0.006{col 58}{space 4}-.5024897{col 71}{space 3}-.0852157
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0027734{col 30}{space 2} .0019917{col 41}{space 1}   -1.39{col 50}{space 3}0.164{col 58}{space 4}-.0066771{col 71}{space 3} .0011303
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1049932{col 30}{space 2} .0624666{col 41}{space 1}   -1.68{col 50}{space 3}0.093{col 58}{space 4}-.2274254{col 71}{space 3}  .017439
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2933266{col 30}{space 2} .0603796{col 41}{space 1}    4.86{col 50}{space 3}0.000{col 58}{space 4} .1749849{col 71}{space 3} .4116684
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2185661{col 30}{space 2} .1956985{col 41}{space 1}    1.12{col 50}{space 3}0.264{col 58}{space 4}-.1649959{col 71}{space 3} .6021282
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0958745{col 30}{space 2} .0715548{col 41}{space 1}    1.34{col 50}{space 3}0.180{col 58}{space 4}-.0443704{col 71}{space 3} .2361194
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2005892{col 30}{space 2}  .144552{col 41}{space 1}    1.39{col 50}{space 3}0.165{col 58}{space 4}-.0827275{col 71}{space 3} .4839058
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1424603{col 30}{space 2} .0832058{col 41}{space 1}    1.71{col 50}{space 3}0.087{col 58}{space 4}  -.02062{col 71}{space 3} .3055406
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2301071{col 30}{space 2} .0576841{col 41}{space 1}    3.99{col 50}{space 3}0.000{col 58}{space 4} .1170483{col 71}{space 3}  .343166
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.2062175{col 30}{space 2} .0467122{col 41}{space 1}   -4.41{col 50}{space 3}0.000{col 58}{space 4}-.2977717{col 71}{space 3}-.1146632
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0779676{col 30}{space 2} .0371276{col 41}{space 1}    2.10{col 50}{space 3}0.036{col 58}{space 4} .0051988{col 71}{space 3} .1507364
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0512801{col 30}{space 2} .0657069{col 41}{space 1}    0.78{col 50}{space 3}0.435{col 58}{space 4}-.0775032{col 71}{space 3} .1800633
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0291723{col 30}{space 2} .3180444{col 41}{space 1}   -0.09{col 50}{space 3}0.927{col 58}{space 4}-.6525278{col 71}{space 3} .5941833
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7487203{col 30}{space 2} .1126605{col 41}{space 1}    6.65{col 50}{space 3}0.000{col 58}{space 4} .5279098{col 71}{space 3} .9695308
{txt}electricity_mean {c |}{col 18}{res}{space 2} .9152351{col 30}{space 2} .1819793{col 41}{space 1}    5.03{col 50}{space 3}0.000{col 58}{space 4} .5585623{col 71}{space 3} 1.271908
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .416803{col 30}{space 2} .1186646{col 41}{space 1}    3.51{col 50}{space 3}0.000{col 58}{space 4} .1842246{col 71}{space 3} .6493813
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3035794{col 30}{space 2} .1044167{col 41}{space 1}    2.91{col 50}{space 3}0.004{col 58}{space 4} .0989263{col 71}{space 3} .5082325
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.3526955{col 30}{space 2} .1991796{col 41}{space 1}   -1.77{col 50}{space 3}0.077{col 58}{space 4}-.7430803{col 71}{space 3} .0376894
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2}-.0060024{col 30}{space 2} .0681822{col 41}{space 1}   -0.09{col 50}{space 3}0.930{col 58}{space 4}-.1396371{col 71}{space 3} .1276322
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}  .048396{col 30}{space 2} .1200952{col 41}{space 1}    0.40{col 50}{space 3}0.687{col 58}{space 4}-.1869863{col 71}{space 3} .2837783
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.0081912{col 30}{space 2} .0854953{col 41}{space 1}   -0.10{col 50}{space 3}0.924{col 58}{space 4}-.1757589{col 71}{space 3} .1593765
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.954996{col 30}{space 2} .4596851{col 41}{space 1}   12.95{col 50}{space 3}0.000{col 58}{space 4} 5.054029{col 71}{space 3} 6.855962
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .67496244
         {txt}sigma_e {c |} {res}  1.292227
             {txt}rho {c |} {res} .21434503{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9 pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,552
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,853

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0331                                         {txt}min = {res}         1
{txt}     between = {res}0.2639                                         {txt}avg = {res}       1.9
{txt}     overall = {res}0.1784                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1115.66
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,853} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0159552{col 30}{space 2} .0442791{col 41}{space 1}    0.36{col 50}{space 3}0.719{col 58}{space 4}-.0708303{col 71}{space 3} .1027406
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2} .0006179{col 30}{space 2} .0003147{col 41}{space 1}    1.96{col 50}{space 3}0.050{col 58}{space 4} 1.02e-06{col 71}{space 3} .0012348
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0133329{col 30}{space 2} .0086084{col 41}{space 1}   -1.55{col 50}{space 3}0.121{col 58}{space 4} -.030205{col 71}{space 3} .0035393
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1081332{col 30}{space 2} .1114216{col 41}{space 1}   -0.97{col 50}{space 3}0.332{col 58}{space 4}-.3265156{col 71}{space 3} .1102492
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0026375{col 30}{space 2} .0018965{col 41}{space 1}   -1.39{col 50}{space 3}0.164{col 58}{space 4}-.0063546{col 71}{space 3} .0010796
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .090951{col 30}{space 2} .0640383{col 41}{space 1}    1.42{col 50}{space 3}0.156{col 58}{space 4}-.0345618{col 71}{space 3} .2164639
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2941931{col 30}{space 2} .0501348{col 41}{space 1}    5.87{col 50}{space 3}0.000{col 58}{space 4} .1959306{col 71}{space 3} .3924555
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3083864{col 30}{space 2} .1105753{col 41}{space 1}    2.79{col 50}{space 3}0.005{col 58}{space 4} .0916628{col 71}{space 3} .5251101
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1713222{col 30}{space 2} .0792425{col 41}{space 1}    2.16{col 50}{space 3}0.031{col 58}{space 4} .0160098{col 71}{space 3} .3266346
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3307182{col 30}{space 2} .1259983{col 41}{space 1}    2.62{col 50}{space 3}0.009{col 58}{space 4} .0837661{col 71}{space 3} .5776702
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2104828{col 30}{space 2} .0901614{col 41}{space 1}    2.33{col 50}{space 3}0.020{col 58}{space 4} .0337697{col 71}{space 3} .3871958
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1941713{col 30}{space 2} .0699837{col 41}{space 1}   -2.77{col 50}{space 3}0.006{col 58}{space 4}-.3313368{col 71}{space 3}-.0570059
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1494425{col 30}{space 2} .0489165{col 41}{space 1}   -3.06{col 50}{space 3}0.002{col 58}{space 4}-.2453171{col 71}{space 3}-.0535679
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0018758{col 30}{space 2} .0018107{col 41}{space 1}    1.04{col 50}{space 3}0.300{col 58}{space 4}-.0016732{col 71}{space 3} .0054247
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0316935{col 30}{space 2} .2397575{col 41}{space 1}    0.13{col 50}{space 3}0.895{col 58}{space 4}-.4382227{col 71}{space 3} .5016096
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0615013{col 30}{space 2} .1394757{col 41}{space 1}    0.44{col 50}{space 3}0.659{col 58}{space 4}-.2118661{col 71}{space 3} .3348687
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3809856{col 30}{space 2} .1013882{col 41}{space 1}    3.76{col 50}{space 3}0.000{col 58}{space 4} .1822685{col 71}{space 3} .5797028
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5407939{col 30}{space 2} .1457543{col 41}{space 1}    3.71{col 50}{space 3}0.000{col 58}{space 4} .2551207{col 71}{space 3} .8264671
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2528299{col 30}{space 2} .1176837{col 41}{space 1}    2.15{col 50}{space 3}0.032{col 58}{space 4}  .022174{col 71}{space 3} .4834858
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4817841{col 30}{space 2} .0897221{col 41}{space 1}    5.37{col 50}{space 3}0.000{col 58}{space 4}  .305932{col 71}{space 3} .6576362
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-1.674819{col 30}{space 2} .3363889{col 41}{space 1}   -4.98{col 50}{space 3}0.000{col 58}{space 4}-2.334129{col 71}{space 3}-1.015509
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0700587{col 30}{space 2} .0544961{col 41}{space 1}    1.29{col 50}{space 3}0.199{col 58}{space 4}-.0367518{col 71}{space 3} .1768691
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .7114338{col 30}{space 2} .0990261{col 41}{space 1}    7.18{col 50}{space 3}0.000{col 58}{space 4} .5173463{col 71}{space 3} .9055213
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.382812{col 30}{space 2} .2452488{col 41}{space 1}   17.87{col 50}{space 3}0.000{col 58}{space 4} 3.902133{col 71}{space 3} 4.863491
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .54954067
         {txt}sigma_e {c |} {res}  1.395771
             {txt}rho {c |} {res} .13420975{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,014
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,108

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0767                                         {txt}min = {res}         1
{txt}     between = {res}0.4172                                         {txt}avg = {res}       3.6
{txt}     overall = {res}0.2601                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}25{txt})     =  {res}  1032.84
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,108} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .1638553{col 30}{space 2} .0332581{col 41}{space 1}    4.93{col 50}{space 3}0.000{col 58}{space 4} .0986707{col 71}{space 3} .2290399
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0056888{col 30}{space 2} .0007142{col 41}{space 1}   -7.97{col 50}{space 3}0.000{col 58}{space 4}-.0070886{col 71}{space 3}-.0042889
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0164291{col 30}{space 2} .0107609{col 41}{space 1}   -1.53{col 50}{space 3}0.127{col 58}{space 4}-.0375201{col 71}{space 3} .0046619
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0513318{col 30}{space 2} .1060031{col 41}{space 1}    0.48{col 50}{space 3}0.628{col 58}{space 4}-.1564304{col 71}{space 3}  .259094
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0018072{col 30}{space 2} .0026342{col 41}{space 1}    0.69{col 50}{space 3}0.493{col 58}{space 4}-.0033558{col 71}{space 3} .0069703
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .162049{col 30}{space 2} .0746017{col 41}{space 1}    2.17{col 50}{space 3}0.030{col 58}{space 4} .0158322{col 71}{space 3} .3082657
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0741274{col 30}{space 2} .0506246{col 41}{space 1}    1.46{col 50}{space 3}0.143{col 58}{space 4} -.025095{col 71}{space 3} .1733498
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0290613{col 30}{space 2} .0694664{col 41}{space 1}    0.42{col 50}{space 3}0.676{col 58}{space 4}-.1070903{col 71}{space 3} .1652129
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2152149{col 30}{space 2} .0677622{col 41}{space 1}    3.18{col 50}{space 3}0.001{col 58}{space 4} .0824035{col 71}{space 3} .3480264
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2101583{col 30}{space 2} .0894077{col 41}{space 1}    2.35{col 50}{space 3}0.019{col 58}{space 4} .0349224{col 71}{space 3} .3853941
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2726633{col 30}{space 2} .0945759{col 41}{space 1}    2.88{col 50}{space 3}0.004{col 58}{space 4}  .087298{col 71}{space 3} .4580287
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2584367{col 30}{space 2} .0663645{col 41}{space 1}    3.89{col 50}{space 3}0.000{col 58}{space 4} .1283647{col 71}{space 3} .3885087
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0084969{col 30}{space 2} .0880754{col 41}{space 1}   -0.10{col 50}{space 3}0.923{col 58}{space 4}-.1811215{col 71}{space 3} .1641276
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0026111{col 30}{space 2} .0134576{col 41}{space 1}   -0.19{col 50}{space 3}0.846{col 58}{space 4}-.0289875{col 71}{space 3} .0237654
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0205902{col 30}{space 2} .1212647{col 41}{space 1}   -0.17{col 50}{space 3}0.865{col 58}{space 4}-.2582646{col 71}{space 3} .2170843
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0670751{col 30}{space 2} .1109152{col 41}{space 1}   -0.60{col 50}{space 3}0.545{col 58}{space 4}-.2844649{col 71}{space 3} .1503146
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .8693821{col 30}{space 2} .1270308{col 41}{space 1}    6.84{col 50}{space 3}0.000{col 58}{space 4} .6204063{col 71}{space 3} 1.118358
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7847683{col 30}{space 2} .1190854{col 41}{space 1}    6.59{col 50}{space 3}0.000{col 58}{space 4} .5513653{col 71}{space 3} 1.018171
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0726465{col 30}{space 2}  .145035{col 41}{space 1}    0.50{col 50}{space 3}0.616{col 58}{space 4} -.211617{col 71}{space 3} .3569099
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0317823{col 30}{space 2} .1040475{col 41}{space 1}   -0.31{col 50}{space 3}0.760{col 58}{space 4}-.2357116{col 71}{space 3} .1721471
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.5382533{col 30}{space 2} .2106141{col 41}{space 1}   -2.56{col 50}{space 3}0.011{col 58}{space 4}-.9510493{col 71}{space 3}-.1254572
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2}-.1384164{col 30}{space 2} .0582721{col 41}{space 1}   -2.38{col 50}{space 3}0.018{col 58}{space 4}-.2526275{col 71}{space 3}-.0242052
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} -.585307{col 30}{space 2} .0653936{col 41}{space 1}   -8.95{col 50}{space 3}0.000{col 58}{space 4}-.7134761{col 71}{space 3}-.4571379
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.4353731{col 30}{space 2} .0651552{col 41}{space 1}   -6.68{col 50}{space 3}0.000{col 58}{space 4} -.563075{col 71}{space 3}-.3076712
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3355312{col 30}{space 2} .0671934{col 41}{space 1}   -4.99{col 50}{space 3}0.000{col 58}{space 4}-.4672278{col 71}{space 3}-.2038345
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.751873{col 30}{space 2} .5277666{col 41}{space 1}   10.90{col 50}{space 3}0.000{col 58}{space 4}  4.71747{col 71}{space 3} 6.786277
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .68488177
         {txt}sigma_e {c |} {res} 1.2333511
             {txt}rho {c |} {res} .23568425{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     1,113
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}       271

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0684                                         {txt}min = {res}         1
{txt}     between = {res}0.3891                                         {txt}avg = {res}       4.1
{txt}     overall = {res}0.2705                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}25{txt})     =  {res}   307.53
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:271} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .1163813{col 30}{space 2} .0541244{col 41}{space 1}    2.15{col 50}{space 3}0.032{col 58}{space 4} .0102995{col 71}{space 3} .2224631
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}  -.00339{col 30}{space 2} .0039773{col 41}{space 1}   -0.85{col 50}{space 3}0.394{col 58}{space 4}-.0111853{col 71}{space 3} .0044053
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.1043117{col 30}{space 2} .0223493{col 41}{space 1}   -4.67{col 50}{space 3}0.000{col 58}{space 4}-.1481155{col 71}{space 3}-.0605079
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .3468085{col 30}{space 2} .2174851{col 41}{space 1}    1.59{col 50}{space 3}0.111{col 58}{space 4}-.0794544{col 71}{space 3} .7730715
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.021165{col 30}{space 2}  .004704{col 41}{space 1}   -4.50{col 50}{space 3}0.000{col 58}{space 4}-.0303847{col 71}{space 3}-.0119453
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3563132{col 30}{space 2} .1306307{col 41}{space 1}    2.73{col 50}{space 3}0.006{col 58}{space 4} .1002819{col 71}{space 3} .6123446
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0963493{col 30}{space 2} .1258348{col 41}{space 1}    0.77{col 50}{space 3}0.444{col 58}{space 4}-.1502824{col 71}{space 3} .3429811
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2247207{col 30}{space 2} .1729553{col 41}{space 1}    1.30{col 50}{space 3}0.194{col 58}{space 4}-.1142655{col 71}{space 3} .5637069
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3344316{col 30}{space 2} .1198946{col 41}{space 1}    2.79{col 50}{space 3}0.005{col 58}{space 4} .0994425{col 71}{space 3} .5694207
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1732636{col 30}{space 2} .1300919{col 41}{space 1}    1.33{col 50}{space 3}0.183{col 58}{space 4}-.0817117{col 71}{space 3}  .428239
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1123571{col 30}{space 2} .0936356{col 41}{space 1}    1.20{col 50}{space 3}0.230{col 58}{space 4}-.0711653{col 71}{space 3} .2958794
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1984198{col 30}{space 2} .1045149{col 41}{space 1}    1.90{col 50}{space 3}0.058{col 58}{space 4}-.0064256{col 71}{space 3} .4032653
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.2520516{col 30}{space 2}  .109231{col 41}{space 1}   -2.31{col 50}{space 3}0.021{col 58}{space 4}-.4661405{col 71}{space 3}-.0379628
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0044393{col 30}{space 2} .0136307{col 41}{space 1}    0.33{col 50}{space 3}0.745{col 58}{space 4}-.0222765{col 71}{space 3}  .031155
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.2798964{col 30}{space 2} .1132952{col 41}{space 1}   -2.47{col 50}{space 3}0.013{col 58}{space 4} -.501951{col 71}{space 3}-.0578418
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .6489858{col 30}{space 2} .3294048{col 41}{space 1}    1.97{col 50}{space 3}0.049{col 58}{space 4} .0033643{col 71}{space 3} 1.294607
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .725053{col 30}{space 2} .2384387{col 41}{space 1}    3.04{col 50}{space 3}0.002{col 58}{space 4} .2577218{col 71}{space 3} 1.192384
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.242628{col 30}{space 2} .2458938{col 41}{space 1}    5.05{col 50}{space 3}0.000{col 58}{space 4} .7606846{col 71}{space 3}  1.72457
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} -.118546{col 30}{space 2} .2128059{col 41}{space 1}   -0.56{col 50}{space 3}0.577{col 58}{space 4} -.535638{col 71}{space 3}  .298546
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1802649{col 30}{space 2} .2236259{col 41}{space 1}    0.81{col 50}{space 3}0.420{col 58}{space 4}-.2580338{col 71}{space 3} .6185635
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-1.680745{col 30}{space 2} .2543045{col 41}{space 1}   -6.61{col 50}{space 3}0.000{col 58}{space 4}-2.179173{col 71}{space 3}-1.182317
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2}-.1191904{col 30}{space 2} .1094954{col 41}{space 1}   -1.09{col 50}{space 3}0.276{col 58}{space 4}-.3337974{col 71}{space 3} .0954167
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.2812536{col 30}{space 2} .1186194{col 41}{space 1}   -2.37{col 50}{space 3}0.018{col 58}{space 4}-.5137432{col 71}{space 3}-.0487639
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0339154{col 30}{space 2} .0919737{col 41}{space 1}    0.37{col 50}{space 3}0.712{col 58}{space 4}-.1463497{col 71}{space 3} .2141806
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.0266278{col 30}{space 2} .1000887{col 41}{space 1}   -0.27{col 50}{space 3}0.790{col 58}{space 4} -.222798{col 71}{space 3} .1695424
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}   9.1588{col 30}{space 2} 1.015736{col 41}{space 1}    9.02{col 50}{space 3}0.000{col 58}{space 4} 7.167994{col 71}{space 3} 11.14961
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .78623261
         {txt}sigma_e {c |} {res} 1.1370872
             {txt}rho {c |} {res} .32345368{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     6,588
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,089

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0757                                         {txt}min = {res}         1
{txt}     between = {res}0.3168                                         {txt}avg = {res}       6.0
{txt}     overall = {res}0.1934                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}27{txt})     =  {res}   983.73
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,089} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0362658{col 30}{space 2} .0243041{col 41}{space 1}    1.49{col 50}{space 3}0.136{col 58}{space 4}-.0113694{col 71}{space 3} .0839009
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2} .0010444{col 30}{space 2} .0014129{col 41}{space 1}    0.74{col 50}{space 3}0.460{col 58}{space 4}-.0017248{col 71}{space 3} .0038136
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0328967{col 30}{space 2}  .009702{col 41}{space 1}   -3.39{col 50}{space 3}0.001{col 58}{space 4}-.0519123{col 71}{space 3} -.013881
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0984195{col 30}{space 2} .0911418{col 41}{space 1}    1.08{col 50}{space 3}0.280{col 58}{space 4}-.0802151{col 71}{space 3} .2770541
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0086459{col 30}{space 2} .0021328{col 41}{space 1}   -4.05{col 50}{space 3}0.000{col 58}{space 4}-.0128262{col 71}{space 3}-.0044656
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0074664{col 30}{space 2} .0553027{col 41}{space 1}    0.14{col 50}{space 3}0.893{col 58}{space 4}-.1009249{col 71}{space 3} .1158578
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2416893{col 30}{space 2} .0516272{col 41}{space 1}    4.68{col 50}{space 3}0.000{col 58}{space 4} .1405018{col 71}{space 3} .3428768
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1523891{col 30}{space 2} .0752587{col 41}{space 1}    2.02{col 50}{space 3}0.043{col 58}{space 4} .0048847{col 71}{space 3} .2998934
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3443268{col 30}{space 2} .0518756{col 41}{space 1}    6.64{col 50}{space 3}0.000{col 58}{space 4} .2426524{col 71}{space 3} .4460012
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4503208{col 30}{space 2} .0536543{col 41}{space 1}    8.39{col 50}{space 3}0.000{col 58}{space 4} .3451603{col 71}{space 3} .5554812
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0551808{col 30}{space 2} .0418335{col 41}{space 1}    1.32{col 50}{space 3}0.187{col 58}{space 4}-.0268115{col 71}{space 3}  .137173
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1439366{col 30}{space 2} .0448014{col 41}{space 1}    3.21{col 50}{space 3}0.001{col 58}{space 4} .0561275{col 71}{space 3} .2317458
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.011591{col 30}{space 2} .0365288{col 41}{space 1}   -0.32{col 50}{space 3}0.751{col 58}{space 4} -.083186{col 71}{space 3}  .060004
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0063751{col 30}{space 2} .0017168{col 41}{space 1}    3.71{col 50}{space 3}0.000{col 58}{space 4} .0030103{col 71}{space 3}   .00974
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.2195497{col 30}{space 2} .0470136{col 41}{space 1}   -4.67{col 50}{space 3}0.000{col 58}{space 4}-.3116947{col 71}{space 3}-.1274046
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1561732{col 30}{space 2}  .143573{col 41}{space 1}    1.09{col 50}{space 3}0.277{col 58}{space 4}-.1252248{col 71}{space 3} .4375711
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .2150247{col 30}{space 2} .1058683{col 41}{space 1}    2.03{col 50}{space 3}0.042{col 58}{space 4} .0075267{col 71}{space 3} .4225227
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4965046{col 30}{space 2} .1362501{col 41}{space 1}    3.64{col 50}{space 3}0.000{col 58}{space 4} .2294594{col 71}{space 3} .7635498
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1608988{col 30}{space 2}  .100512{col 41}{space 1}    1.60{col 50}{space 3}0.109{col 58}{space 4}-.0361011{col 71}{space 3} .3578987
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .372472{col 30}{space 2} .0910524{col 41}{space 1}    4.09{col 50}{space 3}0.000{col 58}{space 4} .1940127{col 71}{space 3} .5509313
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-1.231855{col 30}{space 2} .1558021{col 41}{space 1}   -7.91{col 50}{space 3}0.000{col 58}{space 4}-1.537222{col 71}{space 3}-.9264886
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .1709475{col 30}{space 2} .0543138{col 41}{space 1}    3.15{col 50}{space 3}0.002{col 58}{space 4} .0644945{col 71}{space 3} .2774005
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.2651948{col 30}{space 2} .0596406{col 41}{space 1}   -4.45{col 50}{space 3}0.000{col 58}{space 4}-.3820884{col 71}{space 3}-.1483013
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}   -.1488{col 30}{space 2} .0507075{col 41}{space 1}   -2.93{col 50}{space 3}0.003{col 58}{space 4}-.2481849{col 71}{space 3}-.0494151
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}  .376974{col 30}{space 2} .0499375{col 41}{space 1}    7.55{col 50}{space 3}0.000{col 58}{space 4} .2790982{col 71}{space 3} .4748498
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1951553{col 30}{space 2}  .050336{col 41}{space 1}    3.88{col 50}{space 3}0.000{col 58}{space 4} .0964985{col 71}{space 3}  .293812
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .3900924{col 30}{space 2} .0488093{col 41}{space 1}    7.99{col 50}{space 3}0.000{col 58}{space 4}  .294428{col 71}{space 3} .4857569
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.680406{col 30}{space 2} .4311935{col 41}{space 1}   10.85{col 50}{space 3}0.000{col 58}{space 4} 3.835282{col 71}{space 3}  5.52553
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69397844
         {txt}sigma_e {c |} {res} 1.2196769
             {txt}rho {c |} {res}  .2445672{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S18_balance_imr.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9_dist    $xlist  pdd9_mean_dist sum_dist _cons)
{res}{txt}(note: file S18_balance_imr.rtf not found)
(output written to {browse  `"S18_balance_imr.rtf"'})

{com}. restore
{txt}
{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\lSMS ISA\dofile\Submission\S11_S18_balance.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 5 Apr 2024, 11:09:14
{txt}{.-}
{smcl}
{txt}{sf}{ul off}